RESUMEN
Purpose of the Study: Driving is by far the most common mode of transportation in the United States, but driving ability is known to decline as people experience age-related functional declines. Some older adults respond to such declines by self-limiting their driving to situations with a low perceived risk of crashing, and many people eventually stop driving completely. Previous research has largely focused on individual and interpersonal predictors of driving reduction and cessation (DRC). The purpose of this study was to assess the influence of the transportation environment on DRC. Design and Methods: Data were combined from the Health and Retirement Study, the Urban Mobility Scorecard, and StreetMap North America (GIS data). Longitudinal survival analysis techniques were used to analyze seven waves of data spanning a 12-year period. Results: As roadway density and congestion increased in the environment, the odds of DRC also increased, even after controlling for individual and interpersonal predictors. Other predictors of DRC included demographics, relationship status, health, and household size. Implications: The current study identified an association between the transportation environment and DRC. Future research is needed to determine whether a causal link can be established. If so, modifications to the physical environment (e.g., creating livable communities with goods and services in close proximity) could reduce driving distances in order to improve older drivers' ability to remain engaged in life. In addition, older individuals who wish to age in place should consider how their local transportation environment may affect their quality of life.
Asunto(s)
Envejecimiento , Conducción de Automóvil/estadística & datos numéricos , Ambiente , Transportes , Anciano , Composición Familiar , Femenino , Sistemas de Información Geográfica , Estado de Salud , Humanos , Estudios Longitudinales , Masculino , Estado Civil/estadística & datos numéricos , Riesgo , Análisis de Supervivencia , Estados UnidosRESUMEN
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 Moran's I to measure overall clustering of change and Local Moran's 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 Moran's 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.