Household-level characteristics have been shown to be associated with food insecurity but studies among vulnerable populations are sparse. A food security assessment was developed to determine food security and collect sociodemographic and household level data across San Luis Obispo County. The assessments were administered to vulnerable groups through interviews at multiple sites across the County. Three household characteristics (marital status, number of children in the household and number of workers in the household) were examined in this analysis. A total of 808 surveys were collected, 69% in English and 31% in Spanish. Through ethnicity-stratified sequentially adjusted logistic regression models, the association between food insecurity and household characteristics were tested, controlling for sociodemographic, economic and other potentially mediating variables. In the fully adjusted model for Hispanic/Latino households, associations were observed with number of children in the household and workers in the household, but confidence intervals were wide. In the fully adjusted model for White households, marital status was weakly associated with food insecurity. In both groups, per capita monthly income was strongly associated with food insecurity. Several interrelated household and individual level variables determined a households food security status. Because of this complexity, comprehensive social and economic changes are needed to improve food security in California and the rest of the United States. Also, different processes associated with race/ethnicity and coping strategies with regard to food insecurity should be considered when designing studies, planning policies, and conducting interventions.
Identifer | oai:union.ndltd.org:CALPOLY/oai:digitalcommons.calpoly.edu:theses-2010 |
Date | 01 May 2013 |
Creators | Lund, Alexandra |
Publisher | DigitalCommons@CalPoly |
Source Sets | California Polytechnic State University |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Master's Theses |
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