Impact of social grants on food security : evidence from neighbourhoods in the Gauteng Province of South Africa
Mokwena, Mandisa Nozibele Andrea
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The extent of household food insecurity in South Africa varies from 20 percent to 80 percent, although food security for all citizens is guaranteed in sections 26 and 27 of the constitution. The urban poor face particular challenges especially of increased urbanization, high unemployment, escalating food prices and lack of access to land. The long-held belief that urban households are relatively food secure relative to their rural counterparts has exposed the recent challenges of urban food insecurity in developing countries, also South Africa. Despite all these positive intervention by governments, global food insecurity remains a challenge although the South African government has invested considerable attention to rural support in recent years urban areas has witnessed rampant urban food insecurity. Rural food insecurity has improved in recent years due to concerted interventions placed rural poor households. The urban poor households have experienced an increase in food insecurity despite various government interventions. This study seeks to address the following fundamental question “What influences do social grants have on improving household food security levels in South Africa?” Food security presents many complex approaches with differing approaches for mitigation and South Africa is challenged to explore all these differing views. Hence, the primary aim of this study was to determine the impact of social grants on food security in South Africa. In the process, this study examines and presents the findings of salient factors determining food insecurity of sampled households in Atteridgeville, Soshanguve in the City of Tshwane and Tembisa in Ekurhuleni. This study explored the following objectives:- Firstly, a review of the literature on food security and social security was conducted; secondly, food security literature was extensively reviewed; thirdly, the determinants of food security among households receiving government grants in a suburb of Gauteng were established and lastly available policies and programmes were equally explored to determine the areas for further improvements and their relevance. Primary data collected from a survey of 900 randomly selected poor households were used in the study. Only data from 827 households were used during analysis following the conduct of rigorous coherence tests. Profiling of households in the three locations was essential to identify any effect that social grants might have on food security. Different statistical tools were used in interpretation of results. These include descriptive statistics, correlation analysis, Analysis of Variance and binary logistic regression analysis. Descriptive statistics were used to examine the socio-economic characteristics of the selected households. The USAID developed Household Food Insecurity Access Scale (HFIAS) was used in the study. This scale was used to determine if households became vulnerable to food access in the past 30 days. Basically the scale comprises of nine specific questions which questions the changes that a household has undergone with reference to their diet or consumption patterns that are related to the lack of resources to purchase or produce food. The generic nine HFIAS questions were posed to all households surveyed and their responses were computed and analysed. The administered questionnaire consisted of twenty-seven questions relating to their first-hand experience on food insecurity. This was followed by a frequency of occurrence questions, which determined the regularity of consumption by respondents. The findings of the analysis of variance highlights that there are significant variations in the population means of recipients of social grants by gender and location of beneficiaries. Variances are lowest among those receiving other grants. It is easy to explain this. Other grants cover a support for war veterans, who are disabled or older than 60, and whose numbers are known. It also covers a disability grant, whose eligibility for support has to be proven, perhaps with medical certificates. Qualification for Grant-in-Aid also requires a good amount of documentary support. The fact that there is a minimum variance in the population means of beneficiaries of old age pension is simply due to the fact that it is expected for one to attain a designated old age (60 years and above) in order to qualify. Variances in the population means of food secure households, households experiencing food insecurity and those experiencing the other extreme form of severe food insecurity are significant by categories of social grants that households receive. On the other hand, variances in the population means of mildly food insecure households are significant only among those that receive old age and child grants. These variances increase as the household becomes better food secure in their location. On the contrary variances in the population means of households’ experiences of food insecurity also vary by gender of the head of households; such variances decrease as the household becomes better food secure. This might underpin the important role of women in ensuring low variability in household food security as experiences of food insecurity improves. The study also reports differences in the variances of population means of households by categories of food security. It may also be an indication that social grants may not be directed, in the main, towards food purchases, thus lowering the ability of social grants to creating food secure households in South Africa. The right of citizens to access sufficient food is embedded in sections 26 and 27 of South Africa’s Constitution. In the same light, the 2030 National Development Plan (NDP) outlines food security as an important component to the country’s vision for economic growth. There are particular challenges in relation to urban poverty and rampant urban food insecurity in South Africa. This study contributes to the limited understanding and research on the main determinants of food insecurity among the urban poor and the contribution that social grants can make towards alleviating it. Results from the logistic regression model demonstrate Household income is important in explaining food security. The coefficient of household income is 0.448 and has a p value of 0; the result shows that increases in household income contribute positively to food security. For a one percent increase in income the likelihood of households being food secure increase by 56.5 percentage. Thus, an increase in total income of the household increases the likelihood of being food secure by 56.5 (1.565 -1) percent. In the model under study, the coefficient of the age of household is negative and a p value of 0.001. With a p-value of 0.001, it implies that age does have a significant effect on food security status. The odds ratio of 0.893 suggests that an increase of one unit in age is expected to decrease in the odds of food security by 0.893, holding all other variables constant. This means that an increase in age of the household head decreases the probability of being food secure by 10.7 (0.893 -1) percent. Educated households are expected to have a sustainable supply of food for their families. In this study, education of the household head in each of the three locations is an interaction term between educational attainment of the household head and the specific location under consideration. The education coefficient is 0.065 with a p-value of 0.001 and the odds ratio of 1.067. The p-value indicates that education has a significant impact on food security and the odds ratio confirms that there is a strong association between food security and education. A one percent increase in the level education, the odds of food security increase by 1.067, holding all other variables constant. This means that an increase in level of education tends to increase the likelihood of being food secure by 6.7 (1.067 -1 percent). The study results show there is a significant relationship between the marital status of the household head and household food security. The coefficient of household marital status is 0.503 and has a p-value of 0.002 showing that being married contribute positively to food security. The coefficient of marital status is significantly different from zero. Marital Status has the odds ratio of 1.654, which suggests that being married raises the odds of being food secure. This means that households with a married head are 65.4 percent (1.654-1) more likely to be food secure compared to those headed by unmarried households. The coefficient of household gender is 0.006 and has a p value of 0.278. The coefficient of gender is not significantly different from zero. This suggests that gender has no impact on food security. This means that food security status is similar in male-headed households and those headed by females. Having a backyard garden means that a household can increase their access to food by planting vegetable and other basic food. This variable was used to check if backyard gardens or any other garden could increase the food security status. The coefficient of household backyard garden is -0.71 and has a p-value of 0.669. The coefficient of backyard garden is not significantly different from zero. This suggests that having a backyard garden has no impact on food security. In other words, food security status of households with a backyard garden is similar to those without backyard garden. The coefficient of household Employment Status is 0.551 and has a p value of 0.002, the result shows that being employed contribute positively to food security. The coefficient of employment status is significantly different from zero. Employment Status has the odds ratio of 1.735 which suggest that being employed raises the odds of being food secure, i.e. the presence of food security is strongly associated with being productive and hence employed. Households with employed heads are 73.5 percent (1.735 -1) more likely to be food secure compared with unemployed heads. This is expected, as employment is a stable source of consistent income that can assure a steady supply of food. Three investigated areas may differ due to their structure; Tembisa and Atteridgeville are more of urban townships, while Soshanguve although also urban has a large population of low-income households, compared to the other two suburbs. Thus a dummy variable for location, comparing Soshanguve to other affluent urban townships, was created. The coefficient of household location is -0.415 and has a p-value of 0.017 meaning that the coefficient of geographical location is significantly different from zero. Location has the odds ratio of 0.660 which suggest being located in Soshanguve, compared to being more affluent townships (Tembisa and Atteridgeville) decreases the likelihood of being food secure by 34 (0.66 -1) percent. Households who reside in upmarket location are more likely to be food secure than those from low-income neighbourhoods. The logit regression results displayed that the significant importance of the demographic variables in explaining food security, with four variables being highly significant. These variables include education, household size, marital status, and household income (other market income) all highly significant.