Living in a ‘healthy community’ is everyone’s dream. However today’s communities have been increasingly designed around automobiles instead of pedestrians. Such auto-oriented communities have been questioned and criticised for their impacts on residents’ physical and social health.
In terms of physical health, a substantial body of evidence has shown that automobilecentred communities with segregated land uses, low density, disconnected street networks, and insufficient pedestrian and bicyclist infrastructure are associated with reduced physical activity such as walking or exercise in outdoor spaces.1,2 In contrast, walkable communities with mixed land uses, higher density connected street networks, rich physical activity resources, and pedestrian-friendly designs have been linked to increased physical activity in daily routines.1–4 This environment-physical activity relationship is especially important in the context that obesity has become a leading public health problem in many parts of the world, and physical inactivity is a significant contributing factor 5–8 Traditional approaches of promoting physical activity are focused on personal factors and have not been very successful.9 Recent trends have shifted to a more comprehensive approach, targeting multi-level (personal, social and built environmental) factors.9 This shift came with the increasing popularity of the socio-ecological theory, which considers human behaviour to be influenced by interactive factors on intrapersonal, interpersonal, institutional, community, and public policy levels.10 Community environments, in particular, have been increasingly recognised as important intervention venues, which may help promote sustainable, population-level changes toward more physically active lifestyles. However the actual impacts of moving to walkable communities on residents’ physical activities have not yet been sufficiently studied.
In terms of social health, automobile-oriented communities tend to ignore the needs of pedestrians and make everyday life dependent on automobiles, which in turn reduces opportunities for social encounters and interactions in neighbourhoods. Limited studies suggest that walkable communities promote social health by encouraging walking and other outdoor activities, and thereby, facilitating social interactions among neighbours.11–15 Specific environmental features identified in previous studies include pedestrian-friendly community layout and site design, rich and diverse natural features and opens paces, and mixed land uses providing diverse destinations.11–15 For example, a US study reported a greater sense of community in Kentlands-a prototypic New Urbanist community with walkable environments, compared to a suburban, automobile-oriented development. Kentlands features diverse natural features and open spaces, pedestrian-friendly community layout, and traditional architectural style, as well as many other walkable environmental features.13 Another US study in Portland, Oregon found that residents’ sense of community was greater in a pedestrian-oriented neighbourhood than in an auto-oriented counterpart, and the perception of pedestrian environment is the most significant predictor of sense of community11 Similar results were also found in Galway, Ireland.15 However, some inconsistencies have also been reported on the impacts of certain design features on the sense of community. For example, a study in Atlanta, Georgia reported a negative association between land-use mix and sense of community.16
Growing trends in community development, such as New Urbanism, Smart Growth and Neo-traditional Development all advocate walkability as a guiding principle. The US Green Building Council released the LEED for Neighbourhood Development (LEED-ND) rating system to help guide the development of sustainable and walkable communities. The City of New York released Active Design Guidelines for promoting physical activities through design.17 Recent market studies have also shown growing demands for walkable communities.18–20 In practice, an increasing number of communities are using ‘design’ in addition to ‘programmes’ as the means to promote physical and social health. However, the actual health impacts of such design interventions are understudied.
Study design
This study addresses these knowledge gaps by conducting a case study of Mueller, Austin, Texas to examine its impact on residents’ physical and social health. Mueller is a LEED-ND certified mixed-use community designed to support walking and other outdoor activities. Based on the previous literature, a conceptual framework (Figure 1) is developed for the hypothesised mechanisms of such impacts:
Figure 1:
Conceptual framework for the mechanisms through which environmental changes influence physical activities and social interactions and cohesion
that the increase in community walkability will promote residents’ physical activities and social interactions and cohesion both directly and indirectly (by improving relevant personal attitudes and social support—the mediators), and
that the resulting increases in physical activity and social interactions and cohesion will mutually reinforce each other.
This study explores whether residents had significant increases in their physical activities and social interactions and cohesion after moving to Mueller and, if yes, how these behaviours changed in terms of types, locations and frequencies. Based on findings from this study, a follow-up analysis will use structural equation modeling to examine the whole model to better understand underlying mechanisms for such behaviour changes.
Study setting
Mueller is the first exemplary project by the City of Austin to use a series of innovative policies to create a model for walkable, sustainable and equitable communities. Developed on the former airport site near downtown, Mueller is planned to house 10,000 residents and 10,000 employees. It includes many activity-friendly design features, such as high-density, mixed-land uses, well-connected street networks with sidewalks, and rich and diverse natural resources and open spaces distributed throughout the community (Figure 2 and Table 1). It is also a mixed-income community with over 25% of the housing units being affordable and indistinguishably incorporated into the community with market-rate units. Table 2 illustrates Mueller’s socio-demographic and environmental characteristics, compared to those of the City of Austin. As of May 2013 when this study was conducted, Mueller had about 40% of its property developed, with about 3,500 employees and about 900 single-family households.
Figure 2:
Land use map and developed areas of Mueller community (Source: Catellus)
Table 1:
Mueller’s activity-friendly environmental features
| Activity-friendly location | Activity-friendly neighborhood pattern | Activity-friendly housing |
|---|---|---|
| A central urban location with good connections to public transit and other urban amenities | High density and mixed land uses: Civic/institutional buildings, offices, commercial areas, town centre, parks, open spaces and diverse housing within walkable distances | Eg front porches and rear garages; garden courtyards; vertical mixed use with offices/shops at street level and living units above; access to parks and open spaces; various types of housing |
| Parks and open space: Easily accessible, well-connected and evenly distributed park system (140 acres) with 13 miles of hike/bike paths/lanes | ||
| Streets: Grid-like, hierarchical and well-connected, with complete sidewalks, buffers between sidewalks and streets, traffic calming, and good maintenance, visual quality and surveillance |
Table 2:
Physical environment and population characteristics of Mueller and the City of Austin
| Variables | Features | City of Austin | Mueller community |
|---|---|---|---|
|
| |||
|
Physical environmenta (Mueller’s environments represent a departure from typical community developments in the area) |
Population density (unit: persons/acre) | Mean: 6.8 (SD: 3.7) | 14 |
| Land-use mix | Mean: 0.45 (SD: 0.24) (range: 0–1)b | 10,000 employees; 130,000 residents; 366,000 square feet of retail space | |
| Street connectivity (unit: intersections/100 acres) | Mean: 19.7 (SD: 11.3) | 66 | |
| Sidewalk coverage (unit: %) | Mean: 23.7 (SD: 13.7) | Close to 100 | |
| Parks and open space coverage (unit: %) | Mean: 8.9 (SD: 9.6) | 20 (each household has greenspace within 600 feet) | |
|
| |||
|
Populationc (Mueller’s population is representative of the Austin population) |
% of Hispanic or Latino (of any race) | 31.4% | 35.1% |
| White (one race) | 68.3% | 71.4% | |
| Population under the age of 18 | 22.1% | 21.9% | |
| Mean household income | $68,659 | $66,923 | |
Physical environmental measures for the City of Austin were based on the authors’ previous measures of 74 neighbourhoods (defined as the public elementary school’s attendance area) in Austin.18
The land-use mix measure describes the evenness of land use distribution based on square footage of residential, commercial and office land use.21 The value ranges from 0 (single land use) to 1 (a perfectly even mix).
The population information was obtained from the 2010 Census and the 2005–2009 American Community Survey.22
SD: Standard deviation
Method
Mixed methods, including a focus group (n=13) and an online survey (n=148), were used to triangulate research results in this study A focus group was conducted first to obtain information about Mueller residents’ physical activities and social interactions and cohesion before and after moving into Mueller; and to gain in-depth understanding of the reasons that lead to changes in those behaviours. Focus group results were also used to guide the development of the survey instrument in the following phase. Thirteen participants were recruited at a Mueller Neighbourhood Association meeting. The participants first discussed a series of topics raised by the facilitator; including reasons of moving to Mueller; and comparisons of community environments and behaviours before and after the move. After the discussion, the participants were given a map of Mueller and asked to use coloured stickers and notes to identify destinations they went to for physical and social activities, and places that caused concerns. Content analysis was used to analyse the focus group data.
The online survey was designed for an adult from a household to answer questions about himself/herself and the oldest child in the household, if there was one. It asked about the respondent’s physical activities and social interactions and cohesion (ie the outcome variables) and the child’s physical activities (which were not included in this study), as well as personal, social and built environmental factors that may have influenced these outcomes, before and after moving into Mueller Most of the questions were retrieved from previously validated questionnaires23–25 and several new questions were added based on the focus group results. Pilot tests (n=6) were conducted and led to minor revisions of the questionnaire. The finalised survey took 20–30 minutes to complete.
The subjects were recruited through email invitations to Mueller residents (sent by the developer through its listserve) and online messages posted on the Mueller Community online forum. Reminder messages were posted on the Mueller Community online forum one and two weeks after the initial invitation. Email reminders were not sent out as the developer limits such use of its listserve. After the survey results were collected, valid and complete surveys were included in the analyses using SPSS 19. Descriptive statistics was examined first, and then t-tests were used to examine the pre-post move differences in outcome variables. Pearson correlations matrix was examined to see if there is any significant correlations between changes in physical activities and changes in social interactions and cohesion.
Focus group results
Thirteen subjects (eight females and five males) participated in the focus group session that was carried out in 2013. Three were over 65 years of age; two were in the 50–65-year age group; seven were in the 30–50-year age group; and one was in the 20–30-year range. In terms of ethnicity, there were one African American, one Asian and eleven white participants. Two participants had young children. Residents’ durations of living in Mueller ranged from one month to four years. The content analysis showed increases in physical activity and social interactions and cohesion after moving into Mueller; and the role of some environmental factors in facilitating such changes.
Physical activities.
The majority of the participants reported increased physical activities. They reported that environmental features such as complete and well-connected sidewalks, various parks and open spaces, convenient bike routes, diverse destinations, and safety (eg good street lighting for jogging early in the morning) supported diverse outdoor activities, such as walking, bicycling, jogging, golfing (in a golf course nearby) and flying kites, among many others (Figure 3). Several participants reported walking more since moving to Mueller, and one older lady mentioned walking two or three times more since the move. The participants identified many places to walk to, including parks, greenways, business areas, friends’ homes, block parties, mailboxes and the hospital in the community One participant worked in the community and said she walked to and from work. Two residents liked bicycling and one biked to and from work. Several other residents used public transportation or private cars (with much shorter commute distances now and some carpooling with neighbours) to travel to work. Two participants reported a ‘no driving in Mueller’ rule in their household, and another participant reported a yearly saving of US$1,200 in gasoline for vehicles after moving to Mueller,
Figure 3:
Focus group participants reported environmental features supportive of physical and social activities, such as sidewalks, parks and open spaces, bike routes, diverse destinations, communal facilities, front porches and back alleys shared by small groups (Source: Tom McConnell (images on left), Xuemei Zhu (all other images))
Most of the residents were looking forward to the opening of HEB (a chain supermarket), and plan to do grocery shopping without driving. In addition, the back alleys (see the upper right photo in Figure 3) were often used as shared spaces among a small group of neighbours, and were perceived as safe places for children to play in. A young father proudly said that his four-year-old son learned how to ride a two-wheel bicycle in the back alley He said that the alley had very little through traffic and was safe, which led him to choose this place for teaching his child how to bike.
Social activities and cohesion.
Participants also reported increased social interactions and cohesion due to the changes in community environments. Communal facilities such as community mailboxes were reported by several participants as popular places for social interactions. One resident’s parents liked to go to the mailbox every day, and often came back with stories about new friends they made and news in and around the community Another woman enjoyed the location of her house being close to mailboxes, because that’s how she knew a lot of her neighbours. Several participants reported that smaller backyards encouraged them to use front porches and community outdoor space more often, and thereby have more opportunities to interact with neighbours. Back alleys also played an important role, as they became semi-public areas with multiple functions: the residents hold block parties there, and children also play in the alleys.
Focus group discussions revealed that Mueller has become a close-knit community even with the current partially completed development status. One participant called it “a sun city with diversity”, welcoming people of all ages, ethnicities, income levels, and religions. More importantly, people in Mueller know and help each other: They often share news and exchange favours (eg borrowing tools) with neighbours, pay attention to what is happening in the community, and report concerns, whenever there is any, which had helped to build a safer community.
Map of activities and concerns.
Eleven participants used the maps and coloured stickers that were provided to identify their homes, most-liked places for physical and social activities and places of concern. Popular places for physical and social activities included parks, trails, walking paths, waterfront, pool, restaurants, bank, friends’ homes and the community central activity areas (eg the hangar for farmer’s market). The business area with both big-box retail and small shops received mixed opinions. Commonly mentioned places of concerns were traffic-related. Participants pointed out places that needed safer walking paths and crossing (especially for children), more traffic lights, more speed control and better visibility. A resident stated his safety concerns about the large surface parking in the retail area. One mentioned that big-box retails may not be the type of business they need in Mueller Another resident thought the community park, Lake Park, should be better maintained.
Survey results
A total of 148 valid responses were collected from the online survey, yielding a response rate of 16.4%. The sample included 67% of females and 11% of Hispanics, and had a mean age of 44. In terms of education level, 5.4% had doctoral degrees; 8.8% had professional degrees; 32.0% had master’s degrees; 46.3% had Bachelor’s degrees; and 7.5% had other types of lower education. The household incomes were diverse, with 7.5% in the $200,000 or more category, 12.5% between $150,000 and $199,999, 28.3% between $100,000 and $149,999, 8.3% between $80,000 and $99,999, 12.5% between $60,000 and $79,999, 20.8% between $40,000 and $59,999, and 10% in the $39,999 or lower category. Compared to the 2010 Census information for Mueller, female and non-Hispanic populations were somewhat over-represented in this study.
Physical activity:
After moving to Mueller 70.5% of the respondents had much or somewhat higher levels of physical activity, and 51.6% reported much or somewhat better health. Details about specific types and frequencies of physical activities are listed in Table 3. T-test results showed that all physical activity variables, except the number of days per week with at least 30 minutes of physical activity and time spent on biking per day, had significant (p<0.05) increases after moving to Mueller Meanwhile, time spent in a car reduced by 90 minutes per week. It is worth noting that the time spent on walking in community after moving to Mueller had a mean of 123 minutes (29 minutes per day and 3.9 days per week), which is already very close to the public health guideline for the level of physical activities needed for adults to obtain significant health benefits-at least 150 minutes of moderate-intensity or 75 minutes of vigorous-intensity aerobic physical activity per week, or a combination.5
Table 3:
Descriptive statistics of and t-test results about the pre-post move differences in physical activity and social interactions and cohesion
| Variables | Descriptive statistics | Results of t-test for pre/post differences (Post-move value–pre-move value) |
||||
|---|---|---|---|---|---|---|
| Pre-move mean (SD) |
Post-move mean (SD) |
Mean difference |
t | Degree of freedom |
P value |
|
|
| ||||||
| Days/week with 30+ minutes of physical activity | 3.6 (1.9) | 3.5 (1.7) | −0.2 | −1.05 | 147 | 0.295 |
| Travelling in private car | ||||||
| Days/week | 6.0 (1.6) | 5.7 (1.6) | −0.4 | −2.54 | 140 | 0.012 |
| Minutes/day | 40.8 (25.0) | 27.8 (17.7) | −12.6 | −6.26 | 142 | 0.000 |
| Minutes/weeka | 253.4 (178.9) | 163.9 (120.2) | −90.1 | −6.3 | 140 | 0.000 |
| Total biking | ||||||
| Days/week | 0.5 (1.16) | 0.9 (1.5) | 0.4 | 3.8 | 146 | 0.000 |
| Minutes/day | 34.7 (18.2) | 30.9 (17.2) | 1.8 | 0.5 | 21 | 0.653 |
| Minutes/week | 15.2 (37.4) | 28.8 (58.4) | 13.5 | 3.9 | 144 | 0.000 |
| Total walking | ||||||
| Days/week | 3.4 (2.1) | 4.35 (2.21) | 1.0 | 5.6 | 144 | 0.000 |
| Minutes/day | 26.8 (14.7) | 29.8 (15.2) | 3.7 | 2.8 | 121 | 0.006 |
| Minutes/week | 99.7 (97.4) | 140.0 (115.5) | 39.1 | 4.8 | 138 | 0.000 |
| Walking in community | ||||||
| Days/week | 2.4 (2.2) | 3.9 (2.2) | 1.48 | 7.48 | 144 | 0.000 |
| Minutes/day | 27.0 (14.5) | 29.1 (14.5) | 4.10 | 3.45 | 99 | 0.001 |
| Minutes/week | 74.7 (91.2) | 123.0 (105.5) | 47.7 | 5.59 | 142 | 0.000 |
| Times of social interaction per month | ||||||
| Say hello to neighbours | 10.9 (9.2) | 21.1 (9.8) | 10.1 | 11.6 | 146 | 0.000 |
| Stop and talk to neighbours | 5.6 (6.7) | 13.2 (9.l) | 7.4 | 9.5 | 146 | 0.000 |
| Socialise with neighbours | 1.9 (3.9) | 4.9 (5.9) | 2.9 | 5.6 | 146 | 0.000 |
| Seek help from and exchange favours with neighbours | 1.5 (2.1) | 4.0 (5.2) | 2.5 | 6.2 | 145 | 0.000 |
| Social cohesion b | ||||||
| Neighbours could be counted to help in case of need | 2.3 (8.9) | 4.4 (0.9) | 2.1 | 3.0 | 147 | 0.004 |
| This is a close−knit neighbourhood | 0.8 (12.3) | 4.3 (0.9) | 3.4 | 3.4 | 147 | 0.001 |
The online survey collected information about the number of days per week (continuous variable) and the number of minutes per day (categorical variable with ranges of 1–10, 11–20, 21–30, 31–40, 41–50, 51–60 and 60+) spent on each type of activity. The number of minutes per week was calculated by multiplying the number of days per week with the midpoint value of the time range (or a value of 65 for the ‘60+’ category) for the number of minutes per day
Social cohesion variables were measured on a five-point Likert scale, by asking the respondent about how much he/she agreed or disagreed with the statement (1 = strong disagree, 5 = strongly agree).
The locations of physical activities were examined for their percentages of use and the corresponding pre-post move differences (Figure 4). Neighbourhood streets and sidewalks were the most popular places for physical activity in both pre-move communities and Mueller: About 80% of Mueller residents used them for physical activities. Compared to those in previous communities, the percentages of Mueller residents using neighbourhood streets and sidewalks, parks or trails/paths in a park, greenways/trails/paths not in a park, homes, and natural green spaces or places near water features for physical activities were higher by 18%, 43%, 38%, 22% and 10%, respectively In contrast, the percentage of residents using gyms or fitness facilities for physical activities was 18% lower, likely because of the rich outdoor venues that are freely available in Mueller.
Figure 4.
Percentage of respondents reporting certain locations of physical activity before and after the move
Social interactions and cohesion:
Results also showed that social interactions and cohesion increased significantly after the participants moved to Mueller (Table 3). They ‘say hello to neighbours’, ‘stop and talk to neighbours’, ‘socialise with neighbours in home or restaurant’, and ‘ask for help from or exchange favours with neighbours’ for 10.1, 7.4, 2.5, and 2.9 more times per month, respectively Their perceptions of being in ‘a close-knit neighbourhood’ and neighbours being ‘countable to help in case of need’ were 3.3 and 2.1 points higher respectively, on a five-point scale.
Correlations between increases in physical activity and increases in social interactions and cohesion:
The increase in walking in community correlated significantly with the improved perception rating for ‘neighbours being countable to help in case of need’ (correlation=0.243, p value=0.012) and with the increase in the frequency of ‘saying hello to neighbours’ (correlation=0.315, p value=0.001).
Conclusion
This study has several limitations. First, the survey was conducted online and may not have reached some of the residents who do not use computers and internet frequently in their daily lives. Second, the sample size was relatively small and subject to non-response bias (eg female and non-Hispanic populations being over-represented; residents who were more interested in this topic being more likely to respond to the survey). Third, the pre-move data were collected retrospectively, and were limited to possible recall errors. Finally, the analysis in this paper was limited to bivariate tests, and did not explore the impacts of multilevel factors on changes in physical activity and social interactions and cohesion.
Despite these limitations, this study contributed important knowledge about the ‘actual’ health impacts of moving to a walkable community on residents’ physical and social health. This is an important yet understudied area with significant policy implications. The results from this study provided solid evidence that residents did improve both physical activities and social interactions and cohesion after moving to the walkable environment in Mueller, Austin, Texas. Increased walking in the community correlated with improved social interactions and the perception of social cohesion. The findings also showed a significant reduction in driving among residents, suggesting important environmental benefits that walkable communities can bring by reducing fuel consumption and environmental pollution.
These findings also provided preliminary results that can guide the next step of this study, which is to run a full structural equation model to test the hypothesised mechanisms about how environmental changes influence physical activity and social interactions and cohesion, directly and indirectly through improving relevant personal attitudes and social support.
Contributor Information
Xuemei Zhu, Department of Architecture, Center for Health Systems & Design at Texas A&M University.
Zhipeng Lu, Department of Architecture at Texas A&M.
Chia-Yuan Yu, Urban and Regional Sciences at Texas A&M.
Chanam Lee, Department of Landscape Architecture and Urban Planning at Texas A&M.
George Mann, Department of Architecture, Center for Health Systems & Design at Texas A&M..
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