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Traditional urban neighborhoods with mixed services and good pedestrian access were associated with increased walking among older residents.

We evaluated an intergenerational program bringing together older people and adolescents to examine assumptions underlying intergenerational programming and determine if either generation changed its attitudes toward the other. Program components allowed older people and adolescents to act as either intergenerational helpers or recipients of help. The amount of intergenerational contact prior to participating in the program was examined. Only one group's attitudes changed following participation in the program: adolescents who helped older people showed more enjoyment in being with older people, decreased social distance, and a more positive perception of older people's attitudes toward the young.

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The influence of the physical and social environment on the well-being of a sample of 224 community-residing elderly adults is the focus of this study. Environmental predictors of well-being included house type, neighborhood quality, crime rate, age concentration at the block and census tract levels, distance to services and to city center, and social status of the neighborhood. These predictors were entered into five separate multiple linear regression analyses to determine the extent to which they explained the variance in five indicators of well-being: life satisfaction, activity level, social contacts, neighbor interaction, and neighborhood satisfaction. Personal characteristics of the respondents (sex, age, health, and social class) were controlled in these analyses. Well-being for this sample is associated with living in well-maintained neighborhoods that are primarily residential in character and that are located outside the center of the city.

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Three demonstration projects that developed ways to strengthen the informal helping networks of elderly clients are described. The following aspects of network intervention are discussed and illustrated by these projects: assessment of client networks, possible goals of network intervention and the ability of programs to achieve them, and evaluation of interventions. Each program found barriers to intervening in networks derived from the client, the network, and the social service agency. Major barriers encountered include the client's privacy preferences and attitudes about relying on the network for help, networks that are exhausted or unsupportive, and agency structures that limit interventions. Although each program had some measure of success in strengthening social support for its clients, it does not appear that informal resources can easily and cost effectively substitute for formal services.

Purpose Identify an efficient method of creating a comprehensive and concise measure of the built environment integrating data from geographic information systems (GIS) and the Senior Walking Environmental Assessment Tool (SWEAT). Design Cross-sectional study using a population sample. Setting Eight municipally defined neighborhoods in Portland, Oregon. Subjects Adult residents (N = 120) of audited segments (N = 363). Measures We described built environmental features using SWEAT audits and GIS data. We obtained information on walking behaviors and potential confounders through in-person interviews. Analysis We created two sets of environviental measures, one based on the conceptual framework used to develop SWEAT and another using principal component analysis (PCA). Each measure’s association with walking for transportation and exercise was then assessed and compared using logistic regression. Results A priori measures (destinations, safety, aesthetics, and functionality) and PCA measures (accessibility, comfort/safety, maintenance, and pleasantness) were analogous in conceptual meaning and had similar associations with walking. Walking for transportation was associated with destination accessibility and functional elements, whereas walking for exercise was associated with maintenance of the walking area and protection from traffic. However, only PCA measures consistently reached statistical significance. Conclusion The measures created with PCA were more parsimonious than those created a priori. Performing PCA is an efficient method of combining and scoring SWEAT and GIS data.