These findings provide information about the eleven hypotheses. I have amended each hypothesis to only address the dependent variable food social services, since the question of effects on food insecurity are taken up in Chapter 6 and will be reported in that section. Hypothesis 1 stated: As neighborhood cohesion increases participants will be more likely to utilize food social services, and Part a: Post-relocation decreases in neighborhood cohesion will decrease the likelihood that participants will utilize food social services. The findings indicate support for the null hypothesis. Hypothesis 2 stated: As isolation increases participants will be less likely to utilize food social services, and Part a: Post-relocation increased isolation will decrease participant utilization of food social services. The findings indicate support for the null hypothesis. Hypothesis 3 stated: As fear of crime increases participants will be less likely to utilize food social services, and Part a: Post-relocation increases in fear of crime will decrease the likelihood of participants utilizing food social services. The findings provide support for the null hypothesis. Hypothesis 4 stated: Moving to a mixed-income neighborhood rather than a low- income homogenous neighborhood will decrease the likelihood of food social services
utilization. Moving to a mixed income neighborhood was significantly associated with decrease in food social services utilization. For Hypothesis 5: Pre-relocation, longer tenure in public housing will increase the likelihood that participants will utilize food social services post-
but in an unexpected direction. Rather than increasing the likelihood of utilization of food social services, tenure was associated with a decreased utilization of food social services post-
relocation. I discuss this more in the discussion section. Hypothesis 6 stated: Post-relocation, housing subsidy recipients who have not experienced a disruption in social services network will be more likely to utilize food social services. The findings provide support for the null
hypothesis. Hypothesis 7 stated: Higher self-esteem will increase the likelihood that participants will utilize food social services, and Part a: Post-relocation improvement in self-esteem will increase the likelihood that participants will utilize food social services and decrease food insecurity, and Part b: Alternatively, post-relocation decreases in self-esteem will decrease the likelihood that participants will utilize food social services and increase food insecurity. The findings indicated no significant association between self-esteem and food social services
utilization, which provides support for the null hypothesis. Hypothesis 8 stated: As internal locus of control increases the likelihood that participants will utilize food social services will increase, and Part a: Post-relocation increased internal locus of control will increase the likelihood that participants will utilize food social services. The findings provide support for the null
hypothesis. Hypothesis 9 stated: Higher levels of education will increase the likelihood that participants will utilize food social services. The findings provide support for the null
hypothesis. Hypothesis 10 stated: Better transportation access will increase the likelihood that participants will utilize food social services, and Part a: Post-relocation transportation access will have no effect on utilization of food social services. The findings are different for the two
transportation modes measured, having a car and access to Marta. So, there is support for the null hypothesis in the case of car ownership, since change in car ownership was not significantly associated with food social services utilization. However, Marta access was significantly
associated with food social services utilization. In regards to Part a, our findings indicate that post-relocation access to Marta was significantly associated with food social services utilization, a surprising finding. I discuss the implications of this in the discussion section. Hypothesis 11 stated: Elderly participants will have worse utilization of food social services, and Part a: Post- relocation the elderly will have worse utilization of food social services compared to other households. The findings indicate a significant association between age and food social services utilization, but in an unexpected direction. Increased age was associated with better utilization of food social services, a surprising finding. I will discuss this more in the discussion section.
In summary, the cultural capital variable that was significantly associated with utilization of food social services was Marta accessibility which increased the probability of using food social services, but the effect was buffered by the control variables. Age was significantly associated with increased probability of utilization. Being a widow and better income were significantly associated with decreased probability of utilization (Table 5.1). Two social capital variables significantly decreased the probability of food social services utilization, tenure and moving to a mixed-income neighborhood, but the magnitude of the effect of moving to a mixed-income neighborhood was more than 10 times higher and the effect of tenure was mitigated by the control variables. Some control variables were significant as well. Age and financial strain were significantly associated with increases in utilization, but the magnitude of the effect of financial strain was more than 10 times higher. (Table 5.2). The activist client traits that were significantly associated with decreased food social services utilization were tenure and moving to a mixed- income neighborhood, but the effect of mixed-income was a much higher magnitude (more than 15 times). Better Marta accessibility was significantly associated with increased food social services utilization. The effects of all of the activist client traits were buffered by the control
variables. Age and financial strain were significantly associated with higher food social services utilization. Income was significantly negatively associated with utilization (Table 5.3).