The study of health disparities and the social determinants of health has resulted in the call for public health researchers to investigate the mid- and upstream factors that influence the incidence of chronic diseases (Adler & Rehkopf, 2008; Berkman, 2009; Braveman P. , 2006; Braveman & Gottlieb, 2014; Krieger, 2011; Rose, 1985). Social ecological models (SEMs) provide important conceptual tools to inform this research and practice (Krieger, 2011; Golden & Earp, 2012; Story, Kaphingst, Robinson O'Brien, & Glanz, 2008; Glanz, Rimer, & Lewis, 2002). These models can help us look at the social and physical environments in rural Arizona communities and consider how health policies and environmental interventions address mediating factors, such as disparities in access to fresh food, that contribute to ill health in marginalized, rural, populations. Rural residents are at greater risk for obesity than their urban counterparts (Jackson, Doescher, Jerant, & Hart, 2006; Story, Kaphingst, Robinson O'Brien, & Glanz, 2008). And while human life expectancy has steadily increased over the past thousand years, current projections indicate that the rise in obesity-related illnesses will soon result in its decline (Olshansky, et al., 2005). One reason for this decline, may be the reduced availability of healthy food – an important predictor of positive health outcomes including reduced obesity and chronic disease - in many parts of the United States (Brownson, Haire-Joshu, & Luke, 2006; Ahen, Brown, & Dukas, 2011; Braveman & Gottlieb, 2014; Braveman, Egerter, & Williams, 2011). The United States Department of Agriculture (USDA) defines food deserts as geographic areas in which there is limited access to grocery stores and whose populations have a high rate of poverty. In Arizona, 24% of the rural census tracts are considered food deserts; compared to an average of eight percent of rural census tracts across the nation (United States Department of Agriculture, 2013). Food deserts are one example of the upstream factors influencing the health of rural populations. Local health departments have been encouraged through the National Association for City and County Health Officials (NACCHO) and through the Public Health Accreditation Board (PHAB) to conduct community health assessments (CHAs) in order to identify unique contexts and community resources, health disparities, and the social determinants of health as well as potential areas for advocacy, policy change, environmental interventions, and health promotion interventions. Public health challenges like chronic diseases, which have multiple causes, can be explored in-depth through CHAs. CHAs often contain recommendations for action and/or are followed by community health improvement plans (CHIPs) which help local health departments prioritize resources and set measurable goals. In Florence, AZ recommendations made in a CHA are being acted upon by a non-profit agency, the Future Forward Foundation (3F). This investigation explores two interrelated issues regarding the use of CHAs and CHIPs as practical tools to set public health priorities. First, what makes a CHA useful to rural public health practitioners? What methods of conducting a CHA and subsequently analyzing the data results in actionable policy recommendations and/or environmental level interventions? Second, to what extent can public health agencies engage nontraditional partners to work in partnership to address the social determinants of health? As an example, I will look at the impact of a volunteer-based non-profit agency, located in a rural food desert on improving the social and physical nutrition environment as recommended by a local CHA. This inquiry will provide insights to public health practitioners seeking to identify and implement policy and environmental change addressing complex, multi-causal, public health issues, and provide insights regarding engaging nontraditional partners who may not self-identify as public health agencies.

Backyard gardens has been identified as one of the possible solutions to some of the issues surrounding poverty alleviation in the Bojanala Platinum District Municipality. The main objective of the study was to determine the economic contribution of backyard gardens in alleviation of poverty in rural communities of Bojanala Platinum District Municipality in the North West Province, South Africa. The study used purposive sampling for data collection from the study respondents which enabled the researcher to select a sample with experience and knowledge about the study variables. The questionnaire used as data collection instrument was pretested, validated and subjected to reliability test to improve the efficiency of the use of the questionnaire. The collected data was sorted, coded and analysed using Statistical Package for Social Science (SPSS) Version 23.0 software. Frequency count and percentage were used to summarize the data into tables and graphs. The linear multiple regression model specification was employed to examine the demographic and socio-economic factors (predictors) that influence the generation of income from backyard gardens. Multinomial logistics regression model was also used to determine factors influencing the respondents’ objectives for the Backyard gardens, while the logit regression model was used to analyse determinants of the proportion of backyard land used for backyard farming by respondents/growers. The findings of the study are that: more females (68.2%) were involved in the study than males (31.8%); youth involved in the study were 27.7%; the majority (60.4%) of respondents are in the age group of 41-70 years of age; majority (69.5%) of respondents had matric education, 20.9% had tertiary education, and 3.6% had below matric education whilst 5.9% had no formal education; most of respondents are unemployed (86.6%); 32.2% of respondents are dependent on pension as their source of income, 12.3% depend on grant, 15% depend on monthly salaries, 0.5% depend on investments, 2.3% depend on remittance, and 18.6% depend on piece jobs, whilst 19.1% reported other source of income; majority (99%) of respondents reported that backyard garden contribute a significant proportion to both household income and food security, whilst 1.0% did not agree; 40% of the respondents could not manage to farm the whole garden area, while 60% were able to farm the entire garden area; the majority (70.9%) of respondents provide own solutions to their backyard garden challenges; majority (53.7%) of respondents reported that extension officers never visited their gardens, whilst 46.3% had extension visits on weekly, monthly and quarterly bases; 23.2% of the respondents created permanent employment while 34.1% of them created seasonal employment. The results of the OLS regression analysis showed that gender of respondents, with formal employment, ownership of a farm besides the Backyard garden (BYG) by respondent, farmers’ years of experience in farming and annual income from the sale of livestock by respondent had positive and statistically significant influence on the annual income from Backyard garden with all other factors held constant. The results of the multinomial regression analyses show that a unit change in number of years involved in backyard gardening (YRSBG) does not significantly change the odds of being classified in the 4th category of the outcome variable (Produce to help the needy, the poor, to feed the orphans, and for home based-cares around their communities = 4) relative to the first or second or third categories of the outcome variable, while controlling for the influence of the others. On the other hand a unit change in being employed (EMPLO) and involved in non-farm activities (NFA) do significantly change the odds of being classified in the 4th category of the outcome variable relative to the second or third categories of the outcome variable, while controlling the influence of the others. The Logit coefficient estimate associated with Age, Income per month from BYG, Engage in non-farm activities, Years of experience in gardening, Proportion of produce consumed, having a business plan, Own a farm besides BYG and to lease your backyard have statistically significant impact on respondents area of cultivation for BYG with other factors held constant. Policies to improve BYG in the district should be informed by the aforementioned variables from the results of the inferential analyses. / Agriculture / M. Sc. (Agriculture)