Discrete land uses and transportation walking in two U.S. cities: the Multi-Ethnic Study of Atherosclerosis

Neighborhood factors and survival to old age: The Jackson Heart Study

Few studies have evaluated environmental factors that predict survival to old age. Our study included 913 African American participants in the Jackson Heart Study (JHS) who resided in the tri-county area of the Jackson, MS metropolitan area and were 65-80 years at baseline. Participants were followed from 2000 through 2019 for the outcome of survival to 85 years old. We evaluated each of the following census tract-level measures of the social/physical environment as exposures: socioeconomic status, cohesion, violence, disorder, healthy food stores, residential land use, and walkability. We assessed mediation by physical activity and chronic conditions. As a complementary ecologic analysis, we used census-tract data to examine factors associated with a greater life expectancy. A total of 501 (55%) JHS participants survived to age 85 years or older. Higher social cohesion and greater residential land use were modestly associated with survival to old age (risk difference = 25%, 95% CI: 0-49%; and 4%, 95% CI: 1-7%, respectively). These neighborhood effects were modestly mediated through leisure time physical activity; additionally, social cohesion was mediated through home and yard activity. In our ecologic analysis, a greater percentage of homeowners and a greater proportion of people living in partnered families were associated with higher census-tract level life expectancy. African American older adults living in residential neighborhoods or neighborhoods with high social cohesion were more likely to survive to old age.

The Relationship Between Built Environment and Mental Health of Older Adults: Mediating Effects of Perceptions of Community Cohesion and Community Safety and the Moderating Effect of Income

Many studies revealed a significant correlation between low-density built environment and the mental health of older adults in developed countries. However, scholars and decision-makers recently began to pay close attention to the effect of this relationship in high-density built environments and in developing countries. Using point-of-interest (POI) data from Baidu and data on 20 communities in Guangzhou, China, which were collected through a questionnaire survey, this study aimed to examine the relationship between built environment and the mental health of older adults as well as the physiological–psychological mediating paths between the two, so as to enrich the research on population aging in the high-density urban context in developing countries. The findings indicated that facility accessibility and distance to parks significantly positively correlated with the mental health of older adults and the number of public transit stations, and the distance to these stations significantly negatively correlated with the mental health of older adults. Also, the perceptions of community cohesion and community safety had a significant mediating effect between the built environment and the mental health of older adults. Furthermore, the moderating effect analysis results verified the moderating effect of income: with an increase in income, the perception of community cohesion enhanced the protection of the mental health of older adults and reduced the mediating effect of the perception of community safety. The results provided a reference for policy-makers and urban planners in their efforts to plan and build health-supporting communities and a healthy aging society.

The Effect of High-Density Built Environments on Elderly Individuals' Physical Health: A Cross-Sectional Study in Guangzhou, China

The built environment refers to the objective material environment built by humans in cities for living and production activities. Existing studies have proven that the built environment plays a significant role in human health, but little attention is paid to the elderly in this regard. At the same time, existing studies are mainly concentrated in Western developed countries, and there are few empirical studies in developing countries such as China. Based on POI (point of interest) data and 882 questionnaires collected from 20 neighborhoods in Guangzhou, we employ multilevel linear regression modeling, mediating effect modeling, to explore the path and mechanism of the impact of the built environment on elderly individuals' physical health, especially the mediating effects of physical and social interaction activity. The results show that the number of POIs, the distance to the nearest park and square, and the number of parks and squares are significantly positively correlated with the physical health of the elderly, while the number of bus and subway stations and the distance to the nearest station are significantly negatively correlated. Secondly, physical activity and social networks play a separate role in mediating the effect of the built environment on elderly individuals' physical health. The results enrich the research on the built environment and elderly individuals' health in the context of high-density cities in China and provide some reference basis for actively promoting spatial intervention and cultivating a healthy aging society.

National-level environmental perceptions and walking among urban and rural residents: Informing surveillance of walkability

Built environments that provide activity-friendly routes (e.g., sidewalks) to everyday destinations (e.g., shops) can increase physical activity. Surveillance of supports and destinations is important, and identifying which are associated with walking could prioritize surveillance questions. Our purpose was to identify the significant associations between supports and destinations with walking among a nationally-representative sample of urban- and rural-dwelling adults. Participants in the 2015 National Health Interview Survey, Cancer Control Supplement (n = 29,925) reported the near-home presence of walkable supports (roads, sidewalks, paths, or trails; sidewalks on most streets), destinations (shops; transit; movies, libraries, or churches; relaxing places), and past-week walking for leisure or transportation. We used stepwise logistic regression to quantify associations between supports and destinations and walking, including by urban/rural residence. We calculated the prevalence of walking across counts of reported elements by urban/rural residence. Among all participants, roads, sidewalks, paths, or trails and relaxing destinations were associated with leisure walking. Among urban residents, sidewalks on most streets and all four destination types were associated with transportation walking; among rural residents, roads, sidewalks, paths, or trails; movies, libraries, or churches; and relaxing destinations were associated with transportation walking. Walking was more common when more environmental elements were reported. To improve efficiency, communities may match surveillance priorities to behavioral priorities (i.e., leisure versus transportation walking) and environmental context (i.e., urban/rural areas). Surveillance of environments supporting leisure walking might focus on recreation-oriented spaces. Surveillance of environments supporting transportation walking might differ for urban and rural areas, and assessing destinations may be particularly important.

Land use proportion and walking: Application of isometric substitution analysis

Entropy measures of land use mix are a commonly used component of walkability. However, they present methodological challenges, and studies on their associations with walking have produced mixed findings. This study examined associations of the proportion of discrete land uses with walking, using isometric substitution models that take the complementary nature of land use proportions into account. Analysis of data collected from middle-aged adults living in Brisbane, Australia (n = 10,794) found that replacing residential or other land with commercial land was associated with higher levels of walking. The isometric substitution approach may explain the potential impact of land use changes on residents' walking.

Objectively measured active travel and uses of activity-friendly neighborhood resources: Does change in use relate to change in physical activity and BMI?

Few studies examine how objectively measured use of local physical activity resources contributes to objectively-measured healthy physical activity and weight changes over time. We utilized objective measures to test whether changes in active travel and uses of three physical activity (PA) resources–parks, recreation centers, and transit– related to changes in PA and BMI. Adults (n = 536) in Salt Lake City, UT, wore accelerometer and GPS units in 2012 and 2013, before and after neighborhood rail completion. Regression outcomes included accelerometer counts per minute (cpm), MVPA (moderate-to-vigorous activity minutes/10 h accelerometer wear) and measured BMI; key predictors were changes in active travel and PA resource uses (former and new uses). Significant results (all p < 0.05) showed that increased active travel related to increased total PA (59.86 cpm and 8.50 MVPA); decreased active travel related to decreased MVPA (− 3.01 MVPA). Poorer outcomes were seen after discontinuing use of parks (− 36.29 cpm, − 5.73 MVPA, and + 0.44 BMI points), recreation centers (− 6.18 MVPA), and transit (− 48.14 cpm, − 5.43 MVPA, and + 0.66 BMI). Healthier outcomes were seen after commencing use of parks (29.83 cpm, 5.25 MVPA), recreation centers (44.63 cpm) and transit (38.44 cpm, 4.17 MVPA, and − 0.56 BMI). Transit and park/recreational center uses were unrelated, although park users were more likely to be recreation center users. Active travel and use of three neighborhood PA resources relate to healthy activity and could be fostered by policy and design.

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GPS & accelerometer measures show active travel changes relate to PA changes.

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Increasing park, recreation center, or transit uses relates to more PA.

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Decreasing park, recreation center, or transit uses relates to less PA.

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Changing transit use does not change park or recreation use, and vice versa.

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Policy should enhance active transportation and tie it to recreation options.

Socioeconomic and regional differences in active transportation in Brazil

OBJECTIVE

To present national estimates regarding walking or cycling for commuting in Brazil and in 10 metropolitan regions.

METHODS

By using data from the Health section of 2008’s Pesquisa Nacional por Amostra de Domicílio (Brazil’s National Household Sample Survey), we estimated how often employed people walk or cycle to work, disaggregating our results by sex, age range, education level, household monthly income per capita, urban or rural address, metropolitan regions, and macro-regions in Brazil. Furthermore, we estimated the distribution of this same frequency according to quintiles of household monthly income per capita in each metropolitan region of the country.

RESULTS

A third of the employed men and women walk or cycle from home to work in Brazil. For both sexes, this share decreases as income and education levels rise, and it is higher among younger individuals, especially among those living in rural areas and in the Northeast region of the country. Depending on the metropolitan region, the practice of active transportation is two to five times more frequent among low-income individuals than among high-income individuals.

CONCLUSIONS

Walking or cycling to work in Brazil is most frequent among low-income individuals and the ones living in less economically developed areas. Active transportation evaluation in Brazil provides important information for public health and urban mobility policy-making

Using expert decision-making to establish indicators of urban friendliness for walking environments: a multidisciplinary assessment

BACKGROUND

Numerous studies have suggested that friendly walking environments positively affect physical activity and health. Creating friendly walking environments in urban areas is a complex and wide-ranging topic, and no study has yet established a set of assessment indicators by drawing on the expertise of various disciplines. This study uses a multiple-criteria decision-making technique to elucidate the environmental factors that affect the friendliness of the walking environment.

METHODS

We conducted a two-phase expert questionnaire survey. Experts from the government sector, as well as the academic disciplines of urban planning, transportation, architecture, and landscape design, were recruited to establish a set of walking environment indicators; the degrees of importance assigned to these indicators by the experts were subsequently compared. In phase 1, the fuzzy Delphi method was used by 20 experts, whose responses were used to identify four dimensions and 22 indicators. In phase 2, an analytical network process approach was performed by 16 experts to determine the weights of the dimensions and indicators.

RESULTS

The results revealed that all of the experts ranked the four dimensions in the order of safety > facilities > aesthetics > land use mix. Of the 22 indicators, land use-diversity, land use-access, sidewalk width, sidewalk continuity, and cleanliness were considered the most important.

CONCLUSIONS

The results provide a reference for the management of walking environments by promoting pedestrian-oriented environments and public health.

The Impact of Neighborhoods on CV Risk

Cardiovascular disease (CVD) continues to be the leading cause of death and a major source of health disparities in the Unites States and globally. Efforts to reduce CVD risk and eliminate cardiovascular health disparities have increasingly emphasized the importance of the social determinants of health. Neighborhood environments have emerged as a possible target for prevention and policy efforts. Hence there is a need to better understand the role of neighborhood environments in shaping cardiovascular risk. The MESA (Multi-Ethnic Study of Atherosclerosis) Neighborhood Study provided a unique opportunity to build a comprehensive place-based resource for investigations of associations between specific features of neighborhood physical and social environments and cardiovascular risk factors and outcomes. This review summarizes the approaches used to characterize residential neighborhood environments in the MESA cohort, provides an overview of key findings to date, and discusses challenges and opportunities in neighborhood health effects research. Results to date suggest that neighborhood physical and social environments are related to behavioral and biomedical risk factors for CVD and that cardiovascular prevention efforts may benefit from taking neighborhood context into account.

Built Environment Factors Influencing Walking to School Behaviors: A Comparison between a Small and Large US City

A growing body of evidence supports the association between the built environment and children walking to school (WTS), but few studies have compared WTS behaviors in cities of different sizes. This case-comparison study utilized WTS data from fourth graders in the small city of Manhattan, KS, USA (N = 171, from all eight schools) and data from fourth graders in the large city of Austin, TX, USA (N = 671 from 19 stratified-sampled schools). The same survey instrument was used in both locations. After controlling for socioeconomic and demographic variables, built environment, neighborhood, and attitudinal differences were demonstrated by the odds ratios for WTS in the small city vs. the large city. WTS in the small city was more likely to be associated with walking paths/trails and sidewalk landscape buffers en route to school despite lower perceived neighborhood social cohesion, school bus availability, and parental concerns about crime, compared to WTS in the large city. Also, the small city lacked key pedestrian infrastructure elements that were present in the large city. This study highlights important differences related to WTS behaviors and, thus, provides key insights for encouraging WTS in cities of different sizes.

Neighborhood Walkability and Walking for Transport Among South Asians in the MASALA Study

BACKGROUND

The neighborhood built environment can have a strong influence on physical activity levels, particularly walking for transport. In examining racial/ethnic differences in physical activity, one important and understudied group is South Asians. This study aims to describe the association between neighborhood walkability and walking for transport among South Asian men and women in the United States in the Mediators of Atherosclerosis in South Asians Living in America (MASALA) Study.

METHODS

A cross-sectional study was conducted in 2014 using the baseline dataset of the MASALA study (N = 906). Mean age was 55 years old and 54% of the sample was male. Weekly minutes spent walking for transport was assessed using a questionnaire adapted from the Cross-Cultural Activity Participation Study. Neighborhood walkability was measured using Walk Score, a composite index of walkability.

RESULTS

After adjusting for covariates, with each 10-point increase in Walk Score, South Asian American men engaged in 13 additional minutes per week of walking for transport (P = .008). No association was observed between walkability and walking for transport in South Asian American women.

CONCLUSIONS

Results provide new evidence for how the effects of environmental influences on walking for transport may vary between South Asian men and women.

Multilevel models for evaluating the risk of pedestrian-motor vehicle collisions at intersections and mid-blocks

Walking is a popular form of physical activity associated with clear health benefits. Promoting safe walking for pedestrians requires evaluating the risk of pedestrian-motor vehicle collisions at specific roadway locations in order to identify where road improvements and other interventions may be needed. The objective of this analysis was to estimate the risk of pedestrian collisions at intersections and mid-blocks in Seattle, WA. The study used 2007-2013 pedestrian-motor vehicle collision data from police reports and detailed characteristics of the microenvironment and macroenvironment at intersection and mid-block locations. The primary outcome was the number of pedestrian-motor vehicle collisions over time at each location (incident rate ratio [IRR] and 95% confidence interval [95% CI]). Multilevel mixed effects Poisson models accounted for correlation within and between locations and census blocks over time. Analysis accounted for pedestrian and vehicle activity (e.g., residential density and road classification). In the final multivariable model, intersections with 4 segments or 5 or more segments had higher pedestrian collision rates compared to mid-blocks. Non-residential roads had significantly higher rates than residential roads, with principal arterials having the highest collision rate. The pedestrian collision rate was higher by 9% per 10 feet of street width. Locations with traffic signals had twice the collision rate of locations without a signal and those with marked crosswalks also had a higher rate. Locations with a marked crosswalk also had higher risk of collision. Locations with a one-way road or those with signs encouraging motorists to cede the right-of-way to pedestrians had fewer pedestrian collisions. Collision rates were higher in locations that encourage greater pedestrian activity (more bus use, more fast food restaurants, higher employment, residential, and population densities). Locations with higher intersection density had a lower rate of collisions as did those in areas with higher residential property values. The novel spatiotemporal approach used that integrates road/crossing characteristics with surrounding neighborhood characteristics should help city agencies better identify high-risk locations for further study and analysis. Improving roads and making them safer for pedestrians achieves the public health goals of reducing pedestrian collisions and promoting physical activity.

Modeling spatial segregation and travel cost influences on utilitarian walking: Towards policy intervention

We develop an agent-based model of utilitarian walking and use the model to explore spatial and socioeconomic factors affecting adult utilitarian walking and how travel costs as well as various educational interventions aimed at changing attitudes can alter the prevalence of walking and income differentials in walking. The model is validated against US national data. We contrast realistic and extreme parameter values in our model and test effects of changing these parameters across various segregation and pricing scenarios while allowing for interactions between travel choice and place and for behavioral feedbacks. Results suggest that in addition to income differences in the perceived cost of time, the concentration of mixed land use (differential density of residences and businesses) are important determinants of income differences in walking (high income walk less), whereas safety from crime and income segregation on their own do not have large influences on income differences in walking. We also show the difficulty in altering walking behaviors for higher income groups who are insensitive to price and how adding to the cost of driving could increase the income differential in walking particularly in the context of segregation by income and land use. We show that strategies to decrease positive attitudes towards driving can interact synergistically with shifting cost structures to favor walking in increasing the percent of walking trips. Agent-based models, with their ability to capture dynamic processes and incorporate empirical data, are powerful tools to explore the influence on health behavior from multiple factors and test policy interventions.

The Wisconsin Assessment of the Social and Built Environment (WASABE): a multi-dimensional objective audit instrument for examining neighborhood effects on health

BACKGROUND

Growing evidence suggests that mixed methods approaches to measuring neighborhood effects on health are needed. The Wisconsin Assessment of the Social and Built Environment (WASABE) is an objective audit tool designed as an addition to a statewide household-based health examination survey, the Survey of the Health of Wisconsin (SHOW), to objectively measure participant's neighborhoods.

METHODS

This paper describes the development and implementation of the WASABE and examines the instrument's ability to capture a range of social and built environment features in urban and rural communities. A systematic literature review and formative research were used to create the tool. Inter-rater reliability parameters across items were calculated. Prevalence and density of features were estimated for strata formed according to several sociodemographic and urbanicity factors.

RESULTS

The tool is highly reliable with over 81% of 115 derived items having percent agreement above 95%. It captured variance in neighborhood features in for a diverse sample of SHOW participants. Sidewalk density in neighborhoods surrounding households of participants living at less than 100% of the poverty level was 67% (95% confidence interval, 55-80%) compared to 34% (25-44%) for those living at greater than 400% of the poverty level. Walking and biking trails were present in 29% (19-39%) of participant buffer in urban areas compared to only 7% (2-12%) in rural communities. Significant environmental differences were also observed for white versus non-white, high versus low income, and college graduates versus individuals with lower level of education.

CONCLUSIONS

The WASABE has strong inter-rater reliability and validity properties. It builds on previous work to provide a rigorous and standardized method for systematically gathering objective built and social environmental data in a number of geographic settings. Findings illustrate the complex milieu of built environment features found in participants neighborhoods and have relevance for future research, policy, and community engagement purposes.

How do changes to the built environment influence walking behaviors? A longitudinal study within a university campus in Hong Kong

Background

Previous studies testing the association between the built environment and walking behavior have been largely cross-sectional and have yielded mixed results. This study reports on a natural experiment in which changes to the built environment were implemented at a university campus in Hong Kong. Longitudinal data on walking behaviors were collected using surveys, one before and one after changes to the built environment, to test the influence of changes to the built environment on walking behavior.

Methods

Built environment data are from a university campus in Hong Kong, and include land use, campus bus services, pedestrian network, and population density data collected from campus maps, the university developmental office, and field surveys. Walking behavior data were collected at baseline in March 2012 (n = 198) and after changes to the built environment from the same cohort of subjects in December 2012 (n = 169) using a walking diary. Geographic information systems (GIS) was used to map walking routes and built environment variables, and compare each subject’s walking behaviors and built environment exposure before and after the changes to the built environment. Walking behavior outcomes were changes in: i) walking distance, ii) destination-oriented walking, and iii) walked altitude range. Multivariable linear regression models were used to test for associations between changes to the built environment and changes in walking behaviors.

Results

Greater pedestrian network connectivity predicted longer walking distances and an increased likelihood of walking as a means of transportation. The increased use of recreational (vs. work) buildings, largely located at mid-range altitudes, as well as increased population density predicted greater walking distances.Having more bus services and a greater population density encouraged people to increase their walked altitude range.

Conclusions

In this longitudinal study, changes to the built environment were associated with changes in walking behaviors. Use of GIS combined with walking diaries presents a practical method for mapping and measuring changes in the built environment and walking behaviors, respectively. Additional longitudinal studies can help clarify the relationships between the built environment and walking behaviors identified in this natural experiment.