Jana A. Hirsch

Changes in the Built Environment and Changes in the Amount of Walking Over Time: Longitudinal Results From the Multi-Ethnic Study of Atherosclerosis

Lack of longitudinal research hinders causal inference on the association between the built environment and walking. In the present study, we used data from 6,027 adults in the Multi-Ethnic Study of Atherosclerosis who were 45-84 years of age at baseline to investigate the association of neighborhood built environment with trends in the amount of walking between 2000 and 2012. Walking for transportation and walking for leisure were assessed at baseline and at 3 follow-up visits (median follow-up = 9.15 years). Time-varying built environment measures (measures of population density, land use, number of destinations, bus access, and street connectivity) were created using geographic information systems. We used linear mixed models to estimate the associations between baseline levels of and a change in each built environment feature and a change in the frequency of walking. After adjustment for potential confounders, we found that higher baseline levels of population density, area zoned for retail, social destinations, walking destinations, and street connectivity were associated with greater increases in walking for transportation over time. Higher baseline levels of land zoned for residential use and distance to buses were associated with less pronounced increases (or decreases) in walking for transportation over time. Increases in the number of social destinations, the number of walking destinations, and street connectivity over time were associated with greater increases in walking for transportation. Higher baseline levels of both land zoned for retail and walking destinations were associated with greater increases in leisure walking, but no changes in built environment features were associated with leisure walking. The creation of mixed-use, dense developments may encourage adults to incorporate walking for transportation into their everyday lives.

Generating GPS activity spaces that shed light upon the mobility habits of older adults: a descriptive analysis

BackgroundMeasuring mobility is critical for understanding neighborhood influences on older adults’ health and functioning. Global Positioning Systems (GPS) may represent an important opportunity to measure, describe, and compare mobility patterns in older adults.MethodsWe generated three types of activity spaces (Standard Deviation Ellipse, Minimum Convex Polygon, Daily Path Area) using GPS data from 95 older adults in Vancouver, Canada. Calculated activity space areas and compactness were compared across sociodemographic and resource characteristics.ResultsArea measures derived from the three different approaches to developing activity spaces were highly correlated. Participants who were younger, lived in less walkable neighborhoods, had a valid driver’s license, had access to a vehicle, or had physical support to go outside of their homes had larger activity spaces. Mobility space compactness measures also differed by sociodemographic and resource characteristics.ConclusionsThis research extends the literature by demonstrating that GPS tracking can be used as a valuable tool to better understand the geographic mobility patterns of older adults. This study informs potential ways to maintain older adult independence by identifying factors that influence geographic mobility.

Built environment change and change in BMI and waist circumference: Multi-ethnic Study of Atherosclerosis

To examine longitudinal associations of the neighborhood built environment with objectively measured body mass index (BMI) and waist circumference (WC) in a geographically and racial/ethnically diverse group of adults.

Using MapMyFitness to Place Physical Activity into Neighborhood Context.

It is difficult to obtain detailed information on the context of physical activity at large geographic scales, such as the entire United States, as well as over long periods of time, such as over years. MapMyFitness is a suite of interactive tools for individuals to track their workouts online or using global positioning system in their phones or other wireless trackers. This method article discusses the use of physical activity data tracked using MapMyFitness to examine patterns over space and time. An overview of MapMyFitness, including data tracked, user information, and geographic scope, is explored. We illustrate the utility of MapMyFitness data using tracked physical activity by users in Winston-Salem, NC, USA between 2006 and 2013. Types of physical activities tracked are described, as well as the percent of activities occurring in parks. Strengths of MapMyFitness data include objective data collection, low participant burden, extensive geographic scale, and longitudinal series. Limitations include generalizability, behavioral change as the result of technology use, and potential ethical considerations. MapMyFitness is a powerful tool to investigate patterns of physical activity across large geographic and temporal scales.

Destinations That Older Adults Experience Within Their GPS Activity Spaces Relation to Objectively Measured Physical Activity

Identifying the relevant geography is an ongoing obstacle to effectively evaluating the influence of neighborhood built environment on physical activity. We characterized density and diversity of destinations that 77 older adults experienced within individually representative Global Positioning System (GPS) activity spaces and traditional residential buffers and assessed their associations with accelerometry-measured physical activity. Traditional residential buffers had lower destination density and diversity than activity spaces. Activity spaces based only on pedestrian and bicycling trips had higher destination densities than all-mode activity spaces. Regardless of neighborhood definition, adjusted associations between destinations and physical activity generally failed to reach statistical significance. However, within pedestrian and bicycling-based activity spaces, each additional destination type was associated with 243.3 more steps/day (95% confidence interval (CI) [36.0, 450.7]). Traditional buffers may not accurately portray the geographic space or neighborhood resources experienced by older adults. Pedestrian and bicycling activity spaces elucidate the importance of destinations for facilitating active transportation.

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.

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

This study examines associations of disaggregate land uses with self-reported walking for transportation among participants of the Multi-Ethnic Study of Atherosclerosis (MESA) in Forsyth County, NC and New York, NY. Network distance to each use (in miles), intensity (number of uses per 1/2-mile network buffer) of each use and diversity (number of different uses per 1/2-mile network buffer) of uses were calculated using Geographic Information Systems (GIS). Associations with odds of meeting recommended physical activity levels (150min/week) were examined after controlling for individual- and census-tract-level covariates. Greater distance to and lower intensity of pedestrian-oriented uses, specifically those for social interactions, were associated with lower odds of meeting recommendations in NY. Results suggest that land uses linked to social interactions may be useful for encouraging increased transportation walking.

Factors influencing time-location patterns and their impact on estimates of exposure: the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air)

We assessed time-location patterns and the role of individual- and residential-level characteristics on these patterns within the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air) cohort and also investigated the impact of individual-level time-location patterns on individual-level estimates of exposure to outdoor air pollution. Reported time-location patterns varied significantly by demographic factors such as age, gender, race/ethnicity, income, education, and employment status. On average, Chinese participants reported spending significantly more time indoors and less time outdoors and in transit than White, Black, or Hispanic participants. Using a tiered linear regression approach, we predicted time indoors at home and total time indoors. Our model, developed using forward-selection procedures, explained 43% of the variability in time spent indoors at home, and incorporated demographic, health, lifestyle, and built environment factors. Time-weighted air pollution predictions calculated using recommended time indoors from USEPA overestimated exposures as compared with predictions made with MESA Air participant-specific information. These data fill an important gap in the literature by describing the impact of individual and residential characteristics on time-location patterns and by demonstrating the impact of population-specific data on exposure estimates.

Walkability and cardiometabolic risk factors: Cross-sectional and longitudinal associations from the Multi-Ethnic Study of Atherosclerosis

We used data from 3227 older adults in the Multi-Ethnic Study of Atherosclerosis (2004-2012) to explore cross-sectional and longitudinal associations between walkability and cardiometabolic risk factors. In cross-sectional analyses, linear regression was used to estimate associations of Street Smart Walk Score® with glucose, triglycerides, HDL and LDL cholesterol, systolic and diastolic blood pressure, and waist circumference, while logistic regression was used to estimate associations with odds of metabolic syndrome. Econometric fixed effects models were used to estimate longitudinal associations of changes in walkability with changes in each risk factor among participants who moved residential locations between 2004 and 2012 (n=583). Most cross-sectional and longitudinal associations were small and statistically non-significant. We found limited evidence that higher walkability was cross-sectionally associated with lower blood pressure but that increases in walkability were associated with increases in triglycerides and blood pressure over time. Further research over longer time periods is needed to understand the potential for built environment interventions to improve cardiometabolic health.

How much are built environments changing, and where?: Patterns of change by neighborhood sociodemographic characteristics across seven U.S. metropolitan areas

Investments in neighborhood built environments could increase physical activity and overall health. Disproportionate distribution of these changes in advantaged neighborhoods could inflate health disparities. Little information exists on where changes are occurring. This paper aims to 1) identify changes in the built environment in neighborhoods and 2) investigate associations between high levels of change and sociodemographic characteristics. Using Geographic Information Systems, neighborhood land-use, local destinations (for walking, social engagement, and physical activity), and sociodemographics were characterized in 2000 and 2010 for seven U.S. cities. Linear and change on change models estimated associations of built environment changes with baseline (2000) and change (2010-2000) in sociodemographics. Spatial patterns were assessed using Global Morans I to measure overall clustering of change and Local Morans I to identify statistically significant clusters of high increases surrounded by high increases (HH). Sociodemographic characteristics were compared between HH cluster and other tracts using Analysis of Variance (ANOVA). We observed small land-use changes but increases in the destination types. Greater increases in destinations were associated with higher percentage non-Hispanic whites, percentage households with no vehicle, and median household income. Associations were present for both baseline sociodemographics and changes over time. Greater increases in destinations were associated with lower baseline percentage over 65 but higher increases in percentage over 65 between 2000 and 2010. Global Morans indicated changes were spatially clustered. HH cluster tracts started with a higher percentage non-Hispanic whites and higher percentage of households without vehicles. Between 2000 and 2010, HH cluster tracts experienced increases in percent non-Hispanic white, greater increases in median household income, and larger decreases in percent of households without a vehicle. Changes in the built environment are occurring in neighborhoods across a diverse set of U.S. metropolitan areas, but are patterned such that they may lead to increased health disparities over time.