Yun, Hae Young2015-09-082015-09-082014-07https://hdl.handle.net/11299/174215University of Minnesota Ph.D. dissertation. July 2014. Major: Design, Housing and Apparel. Advisor: Ann Ziebarth. 1 computer file (PDF); x, 185 pages.This study aimed to explore the relationship between demographic characteristics, objective and perceived neighborhood environments, walking behaviors and quality of life among low-income older adults in St. Paul, Minnesota. The conceptual model developed for this study was based on previous research models including the Ecological Model of Health Behaviors by Sallis and colleagues (2008) and Quality of life by Lawton (1991). However, these models cannot explain the relationship between walking behaviors and quality of life. Thus, empirical studies were also considered. For objective neighborhood environments, Pedestrian Environment Quality Index (PEQI) was used to observe the neighborhood environments. Moreover, publicly available data including Part 1 Crimes, traffic accident calls, traffic accidents at intersections, vacant buildings, the number of destinations, land use, and transportation were used to draw maps with Geographical Information System. For this study, the elderly residents living in HUD Section 202 housing were recruited, who are aged 65 years old or over. For the perception of neighborhood environments, accessibility to destinations, comfort and convenience, attractiveness, and safety from traffic and crime were measured with a self-administered survey questionnaire. In the survey questionnaire, demographic characteristics, overall quality of life and walking days in winter and summer were also asked. From the objective neighborhood environment data, it was difficult to judge which neighborhood is more walkable since the neighborhood environments with many destinations have a lot of vehicle accidents, crimes, and vacant buildings, negatively related to walking. Therefore, ANOVA analysis, logistic regression analysis, multiple linear regression analysis, and bivariate analysis were utilized for quantitative analyses. The study findings are as follows: First, quality of life and walking behaviors in winter did not differ by individual housing location; however, walking behaviors in summer were different by grouped housing locations. This may be associated with objective environmental factors including safety (traffic accidents at intersections and crimes) and attractiveness (vacant buildings). Second, the perceptions of neighborhood environments were different by grouped housing locations. In the neighborhoods where the older respondents perceived the highest number of potential destinations, they perceived their neighborhood environments as the lowest attractiveness and safety. Third, the significant factors predicting walking or non-walking were 1) self-rated health (+) and unattractiveness (-) in winter; and 2) attractiveness (+) or unattractiveness (-) in summer. Moreover, more walking was associated with 1) living alone (-) and self-rated health (+) in winter; and 2) traffic accidents at intersections within 400m network buffers (-), self-rated health (+), and utilitarian destinations (+) in summer. Interestingly, self-rated health of older adults were less significant for walking behaviors in summer. Last, the most significant factor expecting better quality of life was better self-rated health. Objective and perceived neighborhood environment factors were not statistically associated with walking but safe and attractive neighborhood environments were associated with more walking. Thus, more walking potentially influences health outcomes and quality of life for older adults for the future. These study findings are implicated policy makers, urban designers and housing developers.enThesis or Dissertation