UNDERSTANDING FACTORS CONTRIBUTING TO HOUSEHOLD FOOD INSECURITY AND POVERTY DYNAMICS IN GERT SIBANDE DISTRICT MPUMALANGA PROVINCE OF SOUTH AFRICA

The challenges posed by the risk of food insecurity, poverty, and hunger have been a major concern in many households in Sub-Saharan Africa and the world at large. This concern is attributable to the negative impacts of the ongoing COVID-19 pandemic, which has led to an increment in food prices and food shortages within South Africa. This study has evaluated the factors contributing to farming households’ food insecurity and poverty in Gert Sibande Municipality of Mpumalanga Province of South Africa. The study was restricted only to two local municipalities out of seven municipalities in Gert Sibande district. A structured questionnaire was administered for data collection. A total of 383 households were involved in the study. Within each municipality, several villages were selected for the survey through the probability random sampling technique. Data were collected between the 23rd of November 2020 and the 25th of January 2021. All responses from the questionnaires were tabulated and processed using Microsoft Excel, Statistical Package for Social Sciences (SPSS) program, and STATA. The Household Food Insecurity Assessment Scale (HFIAS) and Foster-Greer-Thorbecke (FGT) indices were calculated to gauge the households’ food insecurity and poverty status. The HFIAS category indicated that 34.46%, 4.18%, 40.47%, and 20.89% of the households were food secure, mildly, moderately, and severely food insecure, respectively. The FGT poverty index showed that 32.64% of the households were poor while the remainder (67.36%) were categorized as non-poor households. The study applied two regression models: an OLS regression and a logistics regression to identify factors influencing farming households’ food insecurity and poverty status. Factors such as electricity as the cooking energy, growing cereals, being employed, and employment income were negatively associated with food insecurity, whereas housing ownership and access to government child support were positively associated with food insecurity. While household size was positively associated with being poor, employment income, access to social grant, and receipt of remittance were negatively associated with households’ poverty status in the study area. Policy recommendations are made on encouraging younger people to engage in agriculture due to the ageing of farming households. Promoting education and enhancing the standard of education by the government through extension agents could increase the employability of the household heads, thus contributing to improved income for the households. As a larger household size is associated with a higher probability of being poor, endorsing family planning methods for farming households might be needed. Securing multiple sources of livelihood, including both on-farm and off-farm activities, could potentially lead to higher income for the farming households.