Notes on Smallholder Livestock Farmers and Food Security in Raymond Mhlaba

Abstract

The study investigates the role of smallholder livestock farmers in rural household food security in the Raymond Mhlaba Local Municipality, Eastern Cape, South Africa. It adopts a cross-sectional survey of 120 livestock farmers selected via random sampling and analyzes data with SPSS version 22 using descriptive statistics and a binary logistic regression model to identify factors influencing food security among smallholder households. The findings indicate that smallholder livestock farming is profitable and contributes positively to household food security. Cattle production is the most common enterprise, followed by goats and sheep. Based on these findings, the authors recommend strengthening extension services, farmer-based training, and awareness campaigns to improve food security and livelihoods in rural farming communities. Keywords: Smallholder Farming, Livestock, Rural Household, Food Security.

Introduction

In many developing countries, rural households face food insecurity and poverty driven by insufficient food production. Smallholder agriculture is therefore crucial for livelihoods, capable of contributing substantially to family incomes and food security in various contexts. In some countries, smallholders can contribute up to 50% of family income and enhance food security through diversified activities and local production. In South Africa, smallholder farming supports nutritional security and rural employment and offers pathways to local income generation and poverty reduction. Despite these potential benefits, smallholder agriculture in parts of South Africa experiences inefficiencies that limit its ability to alleviate food insecurity, prompting some households to seek off-farm income sources. The literature notes that globally, a large share of smallholder farms concentrate on local food production and consumption, yet challenges persist, including narrow profit margins driven by labour costs, minimum wage policies, limited access to capital, and constrained land expansion. Against this backdrop, this study aims to scrutinise how smallholder livestock farming affects food security in rural households within the Gaga location of Raymond Mhlaba Local Municipality, Eastern Cape. The study builds on a body of work showing the importance of smallholder farming for livelihoods and food security, while acknowledging barriers such as credit access and resource constraints that limit scalability.

Methodology

Study Area and Research Design

The research was conducted in the Gaga location of the Raymond Mhlaba Local Municipality, Eastern Cape, South Africa. Raymond Mhlaba (formerly Nkonkobe) is the largest local municipality in the Amathole District, covering 6,357 km². It has 41,022 households, with 65.3% of the population aged between 15 and 64 years and a dependency ratio of 53.2. Gaga itself has a population of 558 residents in 170 households, within an area of 0.84 km². The broader municipality has a population of 159,516, of which 92.7% are Black African; females constitute 51.8%, and 43.1% are youths aged 15–34. The poverty rate stands at 64.7% and unemployment at 46.7%, with 43.8% having completed some secondary schooling. Despite these challenges, Raymond Mhlaba yields the highest human development index in the Amathole District, with agriculture contributing 8.5% to the local GDP (about R400 million). The study area was chosen due to the prevalence of livestock farmers, available communal grazing, and reliance on both livestock and crop farming. A cross-sectional design was employed to address the research questions.

Data Collection and Sampling Size

Primary data were gathered through a structured questionnaire that allowed both qualitative and quantitative data collection. A combination of purposive and random sampling was used to select participants from the Gaga location, resulting in a sample of 120 livestock farmers who were actively involved in livestock production.

Analytical Framework

The study employs a quantitative approach using a binary logit regression model (BLRM) to examine factors influencing a household’s food security status with livestock ownership. The logit model is appropriate for dichotomous dependent variables (food secure vs. not food secure). The BLRM coefficients estimate odds ratios for the independent variables. The link function relates the dependent variable Z to the probability of the outcome:
\pii = \frac{e^{Zi}}{1+e^{Zi}} Zi = \log\left(\frac{\pii}{1-\pii}\right)
Zi = b0 + b1 X{i1} + b2 X{i2} + \cdots + bp X{ip}
\pii = \frac{e^{Zi}}{1+e^{Zi}} = \frac{1}{1+e^{-Zi}}
\log\left(\frac{\pii}{1-\pii}\right) = \alpha + \beta1 X{i1} + \cdots + \betan X{in} + u_i

Where (\pii) is the probability that the ith household is food secure, and (Zi) is the linear predictor. The predictors (X{ij}) are the twelve explanatory variables selected from prior literature, and the error term is (ui). The study uses the model proposed by Tshikororo, Chauke, and Zuwarimwe (2020) and specifies the following equation for the empirical model:
Y = \alpha + \beta1\text{Age} + \beta2\text{Gender} + \beta3\text{Marital status} + \beta4\text{Household size} + \beta5\text{Educational level} + \beta6\text{Occupation of household head} + \beta7\text{Source of income} + \beta8\text{Farming experience} + \beta9\text{Type of livestock kept} + \beta{10}\text{Access to extension} + \beta{11}\text{Access to credit} + \beta{12}\text{Distance to markets} + \epsilon

The dependent variable, Y, represents whether a household keeps livestock and is food secure (binary 0/1). Twelve predictor variables (X1–X12) are described in Table 1 below, reflecting socio-economic and demographic characteristics of the households. Table 1 summarizes the variables, their measurements, and expected signs.

Results and Discussions

Socio-Economic Characteristics

Table 2 presents the socio-economic characteristics of smallholder farmers in the study area. The age distribution shows that 89% fall within the 38–68 year range, with 11% categorized as youths. Gender distribution reveals 72% male-headed households and 28% female-headed households. Marital status indicates 51% are married, while 49% are not. Education levels show 20% have primary education, 48% secondary, and 32% tertiary. In terms of occupation, 57% are full-time farmers, 26% part-time, and 17% employed. Access to extension services is 42% yes and 58% no, while access to credit stands at 45% yes and 55% no. These results align with broader patterns of gender, education, and access to services observed in South African smallholder studies.

Livestock and Household Implications

Table 3 shows that cattle are the primary livestock kept (52 households, 43%), followed by sheep (42, 35%) and goats (26, 22%), out of 120 sampled households. Respondents indicated that keeping livestock serves as a major source of household income, supports cultural practices, and is perceived as easier to manage—consistent with prior research on livestock’s role in supporting livelihoods and education expenses. The findings also show that households with livestock are more likely to be food secure than those without, corroborating the study’s central hypothesis about the positive link between livestock ownership and food security.

Multivariate Analysis: Factors Influencing Food Security

A multicollinearity check using the Variance Inflation Factor (VIF) yielded a value of 3.4, which is well below the commonly used threshold of 10, indicating no significant multicollinearity among predictors. The pseudo R-squared value is 0.5397, indicating that about 53.97% of the variance in food security is explained by the model. The likelihood ratio Chi-square statistic is 64.82 with a p-value of 0.000, confirming the overall model is statistically significant. The binary logistic regression identified several variables that significantly influence food security: age, marital status, educational level, farming experience, access to credit, and distance to agricultural markets.

Detailed Results (Table 4 Interpretation)

The estimated coefficients (reported in Table 4 as odds ratios in the text) indicate the following directional effects:

  • Age: Positive and significant (p = 0.038), suggesting that each additional year of age is associated with higher odds of being food secure. In the results, the coefficient is reported as approximately 0.088, reflecting an increase in the log-odds with age.

  • Marital status: Positive and marginally significant (p = 0.059), indicating married farmers are more likely to be food secure than unmarried ones.

  • Educational level: Positive and significant (p = 0.045), implying that higher levels of education increase the likelihood of food security; each additional year of schooling corresponds to higher odds of secure status.

  • Farming experience: Highly significant (p = 0.002), with a coefficient around 2.909, indicating that longer farming experience strongly increases the probability of food security.

  • Access to credit: Highly significant (p = 0.005), with a coefficient around 3.718, showing that access to credit substantially raises the odds of being food secure.

  • Distance to agricultural markets: Negative and significant (p = 0.027), with a coefficient around -2.020, suggesting that greater distance to markets reduces the likelihood of food security.
    Other variables (gender, household size, occupation, source of income, type of livestock kept, and extension access) were not statistically significant at conventional levels in this model.

Overall, the results indicate that older, married, better-educated farmers with more farming experience and access to credit, but shorter distances to agricultural markets, are more likely to achieve food security when engaging in smallholder livestock farming. These patterns align with prior research showing the importance of education, experience, and credit access for rural livelihoods, while highlighting the adverse effect of distance to markets on food security outcomes.

Discussion of Key Findings

Age emerged as a positive predictor of food security, suggesting that older household heads have longer engagement with livestock activities, which translates into greater food security stability. Marital status being significant implies that married households may benefit from shared resources and diversified income or labor within the household, contributing to food security. Educational attainment showed a direct relationship with food security, highlighting the role of formal schooling in enhancing farming practices, access to information, and the ability to adapt to market opportunities.
Farming experience had the strongest association with food security, reflecting expertise, risk management, and efficiency in livestock management. Access to credit significantly increased food security odds, underscoring the importance of financial services in enabling households to invest in feeds, veterinary care, or herd improvement. Distance to agricultural markets negatively affected food security, indicating that longer travel distances increase transport costs, reduce market access, and limit timely sale or purchase of inputs, thereby compromising food security.
These findings are consistent with literature on smallholder finance, access to services, and market access barriers in rural Africa and South Africa, reinforcing the need for targeted interventions to strengthen credit markets, education, and market access to improve food security outcomes for livestock farmers.

Conclusion and Recommendations

Rural households in the Eastern Cape face multiple challenges, including unemployment, food insecurity, limited income, and restricted resource access. The study, based on 120 livestock smallholder farmers, finds that male-headed households predominate, with many married and having completed secondary education. The dominant livestock species are cattle, followed by sheep and goats, and the average respondent is around 63 years old. Using a binary logistic regression framework, the study shows that age, marital status, educational level, farming experience, access to credit, and distance to agricultural markets significantly influence food security, with age, marriage, education, and experience positively associated with food security, while distance to markets has a negative association. The results confirm the profitability of smallholder livestock farming and its positive contribution to household food security.

To address identified challenges and bolster rural livelihoods, the study recommends:

  • Strengthening extension services, farmer-focused training, and awareness campaigns on farming practices to enhance household food security and livelihoods.

  • Developing agricultural policies and programs that improve access to extension services and credit for livestock farmers.

  • Implementing targeted interventions to reduce distance-to-market barriers, such as improving market access infrastructure and local marketing opportunities.

  • Encouraging credit facilities tailored to smallholders’ needs, including simplified lending procedures and lower collateral requirements.

  • Integrating education and training programs that boost formal schooling and practical livestock-management skills among farm households.
    Overall, policy and programmatic efforts should aim to improve access to information, finance, and markets for smallholder livestock farmers to sustain food security and livelihoods in rural communities.

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