Thesis (Ph.D. Agricultural (Agricultural Economics)) -- University of Limpopo, 2022 / Regardless of the various measures implemented by the South African government to
curb food insecurity, majority of rural households are still experiencing food insecurity
at the household level. This could be because of the high unemployment rate that the
rural households are experiencing, especially in the Limpopo Province. Despite rural
household members exerting frantic efforts to acquire education, most of them still find
it difficult to secure jobs, which results in them depending on social grants for a living.
Still, social grant money alone is not enough to meet their entire families’ needs,
including food acquisition. The aim of the study was to analyse food security looking
at four dimensions, namely, food availability, access, utilisation, and stability among
rural households of Capricorn and Mopani Districts in the Limpopo Province of South
Africa.
Only two district municipalities in the Limpopo Province, namely, Mopani and
Capricorn Districts, were chosen as areas of study. The two district municipalities were
chosen because, previous studies and reviews reported that these municipalities are
the most affected districts by food insecurity shocks in the Limpopo Province. The
study used a cross-sectional survey, where a Multistage sampling procedure was
employed. The villages were selected based on probability proportionate to size. The
study considered a total of 346 rural households, comprising 173 rural households in
each district municipality. A structured questionnaire was used as an instrument to
collect data from rural households in the study area. In addition, the collected data was
captured using Excel 16. Thereafter, the data was exported to SPSS Version 27 for
analysis. Furthermore, to profile the socio-economic characteristics of households,
assess food consumption patterns and identify the strategies employed to enhance
household food security, descriptive statistics was used. To determine the food
security status of rural households in the study areas, the four dimensions of food
security were analysed separately. For instance, food availability was analysed using
descriptive statistics whereas food accessibility was analysed using Household Food
Insecurity Access Scale [HFIAS]. The HFIAS was also used to identify the food
security status while Household Dietary Diversity Score [HDDS] was used to measure
food utilisation. To measure food stability, a Likert Scale [LS] and descriptive statistics
were used. Multiple Linear Regression Models [MRM] were used to determine the
factors that influenced rural households’ food security status. On the other hand, the
Multinomial Logistic Regression Model [MLRM] was used to examine the determinants
of food security among rural households of Capricorn and Mopani district
municipalities.
The descriptive results established that most rural households from both Mopani
District Municipality [MDM] and Capricorn District Municipality [CDM] consume
different food groups. In this regard, a minority of rural households are classified as
dietary diverse whereas a majority of rural households are still characterised as less
dietary diverse due to the limited consumption of different food groups. This reveals
that these households range from less food secure to moderate food secure, as
illustrated by the food security results. Moreover, the descriptive results also indicated
that a majority of rural households in MDM are classified as severely food insecure
and that food stability was the component contributing to these households being
severely food insecure. As for CDM rural households, the results showed that a
majority of these rural households were moderately food insecure with food availability
and food stability being the contributing component at CDM. The Multiple linear
Regression Model [MRM] results in MDM revealed that the age of the household head,
remittances, and access to credit positively influenced food security status. On the
other hand, the Multinomial Logistic Regression Model [MLRM] results in MDM
revealed that the age of household head, household income greater than R1000,
household income between R1099 to R1999, household income between R4000 to
R4999, income from salary and access to credit, negatively influence food insecurity
status. The Multiple Linear Regression Model confirmed that the male headed
households, age of household head, wages, employment status and household
income negatively influence food security status in CDM. On the contrary, MLRM
results revealed that gender of household head, income from wages, income from
salary, old age pension grant, child support grant, household income above R1000
and access to credit for borrowing money positively influenced the food security status
of rural households in CDM.
In light of this, the study recommends that health practitioners should educate rural
households about healthy eating habits and that having a variety of nutritious food type
may increase food security. The Department of Agriculture should advise rural
households to participate primarily in subsistence farming and that they should focus
their agriculture on crops and livestock. This will enable them to enjoy diverse and
balanced diets. In addition, the government should empower rural households to
participate in development programmes. This may assist households to improve their
livelihoods and may also lead to diverse sources of income, which may enhance food
security. Furthermore, the government can further assist rural households by providing
production inputs (such as seeds/seedlings, fertilizers, and water for irrigation), which
may promote food availability, utilisation and accessibility. / NRF-DAAD
Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:ul/oai:ulspace.ul.ac.za:10386/4225 |
Date | January 2022 |
Creators | Nengovhela, Rudzani |
Contributors | Belete, A., Hlongwane, J. J., Oluwatayo, I. B. |
Source Sets | South African National ETD Portal |
Language | English |
Detected Language | English |
Type | Thesis |
Format | xvi, 139 leaves |
Relation |
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