Anne Vernez Moudon

Association of the Built Environment With Physical Activity and Obesity in Older Persons

OBJECTIVE We examined whether older persons who live in areas that are conducive to walking are more active or less obese than those living in areas where walking is more difficult. METHODS We used data from the Adult Changes in Thought cohort study for a cross-sectional analysis of 936 participants aged 65 to 97 years. The Walkable and Bikable Communities Project previously formulated a walkability score to predict the probability of walking in King County, Washington. Data from the cohort study were linked to the walkability score at the participant level using a geographic information system. Analyses tested for associations between walkability score and activity and body mass index. RESULTS Higher walkability scores were associated with significantly more walking for exercise across buffers (circular zones around each respondents home) of varying radii (for men, odds ratio [OR]=5.86; 95% confidence interval [CI]=1.01, 34.17 to OR=9.14; CI=1.23, 68.11; for women, OR=1.63; CI=0.94, 2.83 to OR=1.77; CI=1.03, 3.04). A trend toward lower body mass index in men living in more walkable neighborhoods did not reach statistical significance. CONCLUSIONS Findings suggest that neighborhood characteristics are associated with the frequency of walking for physical activity in older people. Whether frequency of walking reduces obesity prevalence is less clear.

Walking and Bicycling: An Evaluation of Environmental Audit Instruments

Purpose. This paper reviews existing environmental audit instruments used to capture the walkability and bikability of environments. The review inventories and evaluates individual measures of environmental factors used in these instruments. It synthesizes the current state of knowledge in quantifying the built environment. The paper provides health promotion professionals an understanding of the essential aspects of environments influencing walking and bicycling for both recreational and transportation purposes. It serves as a basis to develop valid and efficient tools to create activity-friendly communities. Data Sources. Keyword searches identified journal articles from the computer-based Academic Citation Databases, including the National Transportation Library, the Web of Science Citation Database, and MEDLINE. Governmental publications and conference proceedings were also searched. Study Inclusion and Exclusion Criteria. All instruments to audit physical environments have been included in this review, considering both recreation- and transportation-related walking and bicycling. Excluded are general methods devised to estimate walking and cycling trips, those used in empirical studies on land use and transportation, and research on walking inside buildings. Data Extraction Methods. Data have been extracted from each instrument using a template of key items developed for this review. The data were examined for quality assurance among three experienced researchers. Data Synthesis. A behavioral model of the built environment guides the synthesis according to three components: the origin and destination of the walk or bike trip, the characteristics of the road traveled, and the characteristics of the areas surrounding the trips origin and destination. These components, combined with the characteristics of the instruments themselves, lead to a classification of the instruments into the four categories of inventory, route quality assessment, area quality assessment, and approaches to estimating latent demand for walking and bicycling. Furthermore, individual variables used in each instrument to measure the environment are grouped into four classes: spatiophysical, spatiobehavioral, spatiopsychosocial, and policy-based. Major Conclusions. Individually, existing instruments rely on selective classes of variables and therefore assess only parts of built environments that affect walking and bicycling. Most of the instruments and individual measures have not been rigorously tested because of a lack of available data on walking and bicycling and because of limited research budgets. Future instrument development will depend on the acquisition of empirical data on walking and bicycling, on inclusion of all three components of the behavioral model, and on consideration of all classes of variables identified.

Correlates of Walking for Transportation or Recreation Purposes

BACKGROUND Walking is a popular recreational activity and a feasible travel mode. Associations exist between walking and the built environment, but knowledge is lacking about specific environmental conditions associated with different purposes of walking. METHODS This cross-sectional study used a survey of 438 adults and objective environmental measures. Multinomial logit models estimated the odds of walking for recreation or transportation purposes. RESULTS Utilitarian destinations were positively associated with transportation walking, but recreational destinations were not associated with any walking. Residential density was correlated with both purposes of walking, and sidewalks with recreation walking only. Hills were positively associated with recreation walking and negatively with transportation walking. CONCLUSIONS Physical environment contributed significantly to explain the probability of walking. However, different attributes of environment were related to transportation versus recreation walking, suggesting the need for multiple and targeted interventions to effectively support walking.

Operational Definitions of Walkable Neighborhood: Theoretical and Empirical Insights

BACKGROUND The concept of walkable neighborhoods is increasingly important in physical activity research and intervention. However, limited theoretical understanding and measurable definitions remain a challenge. METHODS This paper reviews theories defining neighborhoods and offers an empirical approach to identify measurable attributes and thresholds of walkable neighborhoods. Bivariate and multivariate analyses are used for self-reported socio-demographic background, neighborhood walking behavior and perception, and objective measures of environments. RESULTS Environmental attributes positively associated with walking sufficiently to meet health recommendations included higher residential density and smaller street-blocks around home, and shorter distances to food and daily retail facilities from home. Threshold distances for eating/drinking establishments and grocery stores were 860 and 1445 feet. CONCLUSIONS Results questioned theoretical constructs of neighborhoods centered on recreation and educational uses. They pointed to finer mixes of uses than those characterizing suburban neighborhoods, and small spatial units of analysis and intervention to capture and promote neighborhood walkability.

PHYSICAL ACTIVITY AND ENVIRONMENT RESEARCH IN THE HEALTH FIELD: IMPLICATIONS FOR URBAN AND TRANSPORTATION PLANNING PRACTICE AND RESEARCH

This article reviews literature fromthe health field investigating the characteristics of environments that support or hinder physical activity. This literature shows that physical activity is associated with objective and subjective measures of accessibility to recreational facilities and local destinations, as well as with neighborhood safety and visual quality. Walking and biking emerge as prominent forms of physical activity and occur primarily in neighborhood streets and public facilities, suggesting that building walkable and bikable communities can address health as well as transportation concerns. The studies help advance environment-behavior research related to urban and transportation planning. They identify behavioral and environmental determinants of physical activity and employ rigorous data collection methods and theoretical frameworks that are new to the planning field. The article concludes that multidisciplinary research will likely yield promising results in identifying the aspects of environments that can be modified to encourage physical activity and physically active travel.

SITE DESIGN AND PEDESTRIAN TRAVEL

Research findings are summarized regarding the relationship between site design and pedestrian travel in mixed-use, medium-density environments, and recommendations are set forth for improving pedestrian facilities in suburban neighborhoods. A quasi-experimental method is used to study pedestrian volumes into 12 neighborhood commercial centers in the central Puget Sound region. Sites were matched for population density, land use mix, and income, but they varied in terms of neighborhood site design as measured by block size, and by the length and completeness of sidewalk systems. Urban sites with small blocks and extensive sidewalk systems were found to have, on average, three times the pedestrian volumes of suburban sites with large blocks and short, incomplete sidewalk systems. There are, however, many suburban pedestrians, with volumes varying between 50 and 103 people per hour walking into the suburban commercial centers studied. The majority of suburban pedestrians use streets with sidewalks where available. Also, suburban pedestrians are more likely both to jaywalk and to use crosswalks than their urban counterparts. People under age 18 and people of color were overrepresented in suburban pedestrian populations compared with their makeup in the local residential population. These findings point to the importance of providing facilities to improve pedestrian safety for people who cannot or do not want to drive in such areas. Recommendations include completing sidewalk networks, creating walkways to connect all building entrances to public sidewalks, and increasing the opportunities for pedestrians to cross streets safely.

EFFECTS OF SITE DESIGN ON PEDESTRIAN TRAVEL IN MIXED-USE, MEDIUM-DENSITY ENVIRONMENTS

Whether high or low incidence of pedestrian travel in mixed-use, medium-density environments is due to site design characteristics, and specifically to presence of direct, continuous, and safe pedestrian systems, is examined. Twelve neighborhood centers or sites in the Puget Sound area of Washington were selected by matching gross residential density, median income, automobile ownership, and intensity and type of neighborhood commercial development. Pedestrians and bicyclists were recorded that traveled into the commercial area. A clear break emerges between urban and suburban sites. The average urban pedestrian volume is 37.7 pedestrians per hour per 1,000 residents, which is 3 times higher than the 12.5 pedestrians per hour per 1,000 residents in suburban sites. These results strongly support the hypothesis that, when holding other variables constant, the urban versus suburban difference in route directness and completeness of pedestrian facilities (namely, block size and sidewalk length) affects pedestrian volumes. The research also questions the common belief that people do not walk in the suburbs. Given appropriate land use conditions, pedestrian facility improvement programs in suburban areas can support pedestrian travel and have a significant influence on mode choice.

Obesity and Supermarket Access: Proximity or Price?

OBJECTIVES We examined whether physical proximity to supermarkets or supermarket price was more strongly associated with obesity risk. METHODS The Seattle Obesity Study (SOS) collected and geocoded data on home addresses and food shopping destinations for a representative sample of adult residents of King County, Washington. Supermarkets were stratified into 3 price levels based on average cost of the market basket. Sociodemographic and health data were obtained from a telephone survey. Modified Poisson regression was used to test the associations between obesity and supermarket variables. RESULTS Only 1 in 7 respondents reported shopping at the nearest supermarket. The risk of obesity was not associated with street network distances between home and the nearest supermarket or the supermarket that SOS participants reported as their primary food source. The type of supermarket, by price, was found to be inversely and significantly associated with obesity rates, even after adjusting for individual-level sociodemographic and lifestyle variables, and proximity measures (adjusted relative risk=0.34; 95% confidence interval=0.19, 0.63) CONCLUSIONS Improving physical access to supermarkets may be one strategy to deal with the obesity epidemic; improving economic access to healthy foods is another.

Protective association between neighborhood walkability and depression in older men

OBJECTIVES: To evaluate the association between neighborhood walkability and depression in older adults.

Using built environment characteristics to predict walking for exercise

BackgroundEnvironments conducive to walking may help people avoid sedentary lifestyles and associated diseases. Recent studies developed walkability models combining several built environment characteristics to optimally predict walking. Developing and testing such models with the same data could lead to overestimating ones ability to predict walking in an independent sample of the population. More accurate estimates of model fit can be obtained by splitting a single study population into training and validation sets (holdout approach) or through developing and evaluating models in different populations. We used these two approaches to test whether built environment characteristics near the home predict walking for exercise. Study participants lived in western Washington State and were adult members of a health maintenance organization. The physical activity data used in this study were collected by telephone interview and were selected for their relevance to cardiovascular disease. In order to limit confounding by prior health conditions, the sample was restricted to participants in good self-reported health and without a documented history of cardiovascular disease.ResultsFor 1,608 participants meeting the inclusion criteria, the mean age was 64 years, 90 percent were white, 37 percent had a college degree, and 62 percent of participants reported that they walked for exercise. Single built environment characteristics, such as residential density or connectivity, did not significantly predict walking for exercise. Regression models using multiple built environment characteristics to predict walking were not successful at predicting walking for exercise in an independent population sample. In the validation set, none of the logistic models had a C-statistic confidence interval excluding the null value of 0.5, and none of the linear models explained more than one percent of the variance in time spent walking for exercise. We did not detect significant differences in walking for exercise among census areas or postal codes, which were used as proxies for neighborhoods.ConclusionNone of the built environment characteristics significantly predicted walking for exercise, nor did combinations of these characteristics predict walking for exercise when tested using a holdout approach. These results reflect a lack of neighborhood-level variation in walking for exercise for the population studied.